Object tracking system optimization and optimizers

ABSTRACT

Systems, methods and software products optimize installation and operation of an object tracking system. Performance of the athlete tracking system is continually monitored and optimized based upon one or more of: statically positioned tags, grouping tags within two or more tag sets to assign ping rates, selecting receiver configuration and aim dynamically based upon environmental and situational conditions. Tracking tags are improved to facilitate coupling of the tag to an athlete and may be self-configurable. A trackable protection pad allows a tracking tag to be positioned substantially horizontal when the athlete is competing. A data replay tool replays location tracking information in chronological order and visually plots location of tracking tags and errors in the determined location. A tag manager automatically configures the tracking tags. A robotic vehicle automated installation of the object tracking system.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/960,026, filed Dec. 4, 2015, which is a continuation of InternationalPatent Application No. PCT/US2014/040914, filed Jun. 4, 2014, whichclaims priority to US Provisional Patent Application No. 61/830,961titled “Athlete Tracking System Improvements and Tools,” filed Jun. 4,2013, US Provisional Patent Application No. 61/900,786 titled “ObjectTracking Systems With Automatic Optimization And Associated Methods,”filed Nov. 6, 2013, US Provisional Patent Application No. 61/930,378titled “Object Tracking Systems With Automatic Optimization AndAssociated Methods,” filed Jan. 22, 2014, US Provisional PatentApplication No. 61/945,559 titled “Automated Installation AndCalibration Systems and Methods For An Object Tracking System,” filedFeb. 27, 2014, and US Provisional Patent Application No. 61/971,940titled “Automatic Object Tracking System Optimizer And AssociatedMethods,” filed Mar. 28, 2014. Each of the above referenced applicationsis incorporated herein by reference.

BACKGROUND

Commercially available Ultra-WideBand (UWB) tags are designed to meetthe common demands of environments such as hospitals, manufacturing andinventory tracking. One of the major requirements for operating in theseenvironments is an extended operating life. Extended operating liferequires a large battery size, thereby resulting in a larger overallsize of the tracking tag. Further, the tracking tag is enclosed within awaterproof protective casing that has an access door to allowreplacement of the battery. To ensure that the case is waterproof, theaccess door typically includes a seal. The device includes a batteryholder that allows the battery to be replaced. All these features resultin a relatively large tracking tag. Large tracking tags are adistraction to, and have an influence on, the object being tracked.

Installation, configuration, and calibration of an RF tag based objecttracking system for use in a sports environment is a labor intensive anditerative process that requires expert knowledge. Receivers are firstinstalled around a perimeter of the sports environment and each receiveris manually aimed, by eye, at a predetermined location within thesporting environment such that uniform coverage of a specific region ofthe sports environment (e.g., a portion of a playing surface) isachieved. An initial system performance evaluation is completed byrecording and manually analyzing location data determined by the objecttracking system for an RF tag placed on a technician as he/she walks apredetermined path within the sports environment. The predetermined pathis designed to establish receiver coverage of the sports environment bythe object tracking system. The RF tag is placed in such a way that itis free of obstruction by the technician's body (e.g., the tag is on topof a hat worn by the technician).

This recording and manual analysis process is iteratively repeated,typically using three different paths of increasing granularity. Afteranalyzing the location data from a current path, the technician willeither manually adjust one or both of pan and tilt of one or morereceivers and repeat the current path, or continue the process byperforming the next path.

This approach requires that the technician has a system expert'sintimate knowledge of receiver characteristics and associated skill toextract information from the location data recorded for each test path.The expert knowledge required is at a very high premium and theapplication of the knowledge varies from technician to technician.

Thus, installation of an RF tag based object tracking system (a)requires highly specific expert knowledge, (b) is time intensive, (c) isa labor intensive incremental adjustment process, (d) may result in theRF tag based object tracking system operating at adequate but notoptimal performance, and (e) result in inconsistent performance frominstallation to installation.

Any given sports environment easily includes hundreds of athletes andother objects that are tracked by an object tracking system, where eachathlete and/or object is configured with at least one tracking tag thattransmits a wireless signal (ping) that is located by the objecttracking system. While such tracking systems may be optimized for thesports environment during installation, such systems do notautomatically monitor and/or optimize their performance duringoperation.

Receivers of an RF tag based object tracking system are positionedaround an area of interest such that each receiver covers a portion ofthe area of interest and in combination the receivers cover all of thearea of interest. For a sports environment, the tracked area is forexample a field of play and may include sideline areas.

During installation, each receiver is configured with a single, fixed,set of characteristics that are selected to enable the receiver todetect “pings” (i.e. low power signal transmissions) transmitted fromone or more RF tags located within a defined portion of the area ofinterest that is assigned to that receiver based upon anticipatedenvironmental conditions. For example, one receiver may be configuredwith a high gain antenna and matching analog conditioning circuitry thatincludes a six-point-five GHz band pass filter.

In practice, the sports environment is subjected to continual change,both environmental and situational. Environmental changes within thesports environment include the introduction of powerful electromagneticsignals (e.g. Wi-Fi or wireless broadcast camera signal). Since the RFtag based object tracking system is based upon the receivers detectingpings from the RF tags, changes in the spectral content of the sportsenvironment are often catastrophic upon the system's ability to locatethe RF tags.

Situational changes (e.g., movement of the RF tags within the sportsenvironment) result in changes of RF tag density (i.e., the number oftags within a certain area), and thereby changes in the amount and/orfrequency of pings received by each receiver of the object trackingsystem. The static configuration of each receiver is selected to alsoadequately cover anticipated situational changes. Although situationalchanges are not usually catastrophic to locating the RF tags, tuning theobject tracking system to handle worst case tag/ping densities comes atthe expense of system performance in other areas. These changingsituations and environmental conditions are problematic because thereceivers are statically configured for optimal performance underspecific conditions.

Since each receiver configuration is static, the object tracking systemcannot perform optimally for all environmental and situationalconditions. The dynamically changing environmental and situationalconditions places constantly changing demands on each receiver. Thesedemands make it impossible to consistently achieve optimal performanceof the object tracking system since it is statically configured to meetonly certain of these environmental and situational conditions.

Exacerbating this problem, the likelihood of environmental andsituational changes is greatest on “Game Day” when the integrity of theobject tracking system is most crucial.

In an attempt to have the object tracking system operate reliably on“Game Day,” all environmental and situational conditions likely to existon “Game Day” are anticipated and receivers of the object trackingsystem are configured in anticipation of these conditions. Thespecialized configuration (e.g., additional circuitry) required tooperate effectively with the anticipated conditions often have negativeeffects under different conditions. Therefore, when the object trackingsystem is statically configured to meet all anticipated “worst case”conditions, the object tracking system invariably has inherentlysub-optimal performance when these anticipated conditions are notprevailing.

Further, where “game day” conditions are not fully anticipated, acatastrophic failure to determine locations of the RF tags may stilloccur within the object tracking system when such unanticipatedconditions occur. Such catastrophic failure typically terminatesoperation of the object tracking system and requires a team oftechnicians to visit the stadium to physically swap out the installedreceivers for receivers configured to handle the unanticipatedconditions—if identified. Such receiver replacement is costly and timeconsuming and addresses the current environmental condition. However,such receiver replacement does not take into account any futureunanticipated conditions that the system will be ill-equipped to handle.

SUMMARY OF THE INVENTION

An Improved Tracking Tag

In one embodiment, an ultra-wide band tracking tag for use in sportsincludes a partial housing having an open lower portion, a batterycoupled directly to a printed circuit board, a potting compound forpotting the printed circuit board and battery within the partial housingto make the tag waterproof, a sealing compound for protecting sensitivecomponents positioned on the printed circuit board from the pottingcompound, and one or more straps attached to the partial housing tofacilitate coupling of the tag to an athlete.

In another embodiment, a UWB tracking tag is configured for attachmentto an athlete and includes a UWB transceiver, a battery, and two or morestraps for coupling the tag to the athlete.

Trackable Protection Pad

In one embodiment, a trackable protection pad for use by an athleteincludes a first tracking tag configured with the protection pad and ispositioned such that the first tracking tag is substantially horizontalwhen the athlete is competing.

Location Data Visualization

In one embodiment, a data replay tool replays location trackinginformation, and includes a replay module having machine readableinstructions stored within memory that when executed by a processorsends the location tracking information in chronological order to one ora plurality of visual display tools.

In another embodiment, a computer implemented tool visually displaysperformance of an athlete tracking system that generates trackingposition information for each signal received from a tracking taglocated within a tracking area. The tracking position informationincludes a determined location, a position error, and a timestamp. Thetool includes a visual plotting module having machine readableinstructions stored within memory and executed by a processor toperform, for each signal transmitted by the tracking tag, the step of:displaying a symbol on a graphical representation of the tracking areaat a position representing the location of the tag within the trackingarea, wherein the symbol is selected based upon one or more of: (a) theaccuracy of the determined location based upon the receiver events, and(b) errors in the determined location.

Receiver Modifications

In one embodiment, a receiver detects a UWB tracking tag in a game dayenvironment and includes a wireless receiver for receiving a signal fromthe tracking tag, and a band pass filter centered at a center frequencyof the signal and inserted immediately after the antenna. The band passfilter reduces the effect of noise from the game day environment withinthe wireless receiver.

Tag Manager

In one embodiment, a tag manager configures an athlete tracking system.The tag manager includes software, stored within memory of a portablecomputing device configured with a wireless transceiver forcommunicating with a tracking tag associated with an athlete tracked bythe athlete tracking system, that when executed by a processor of theportable computing device implement the steps of: automaticallyassigning a tag ID of the tracking tag to the athlete within a rosterlist, and communicating the roster list to the athlete tracking system.

Continuous Accuracy Measurement

In one embodiment, a method continuously evaluates performance of anathlete tracking system. The athlete tracking system determines thelocation of a test tag fixedly positioned within a tracking area of theathlete tracking system and a positioning error of the athlete trackingsystem is determined based upon a difference between the determinedlocation and a known location of the test tag.

Object Tracking System Optimization

In one embodiment, a method automatically optimizes performance of anobject tracking system. An optimizer receives locations of each of aplurality of tags, where each tag is attached to an object tracked bythe object tracking system. Identifiers of the tags are grouped withintwo or more tag sets and each tag identified within a first tag set ofthe two or more tag sets is configured with a first ping rate and tagsidentified within the other tags sets of the two or more tag sets areconfigured with a second ping rate. The first ping rate is higher thanthe second ping rate.

In another embodiment, a software product has instructions, stored oncomputer-readable media, wherein the instructions, when executed by acomputer, perform steps for automatically optimizing performance of anobject tracking system. The software product includes instructions forreceiving locations of each of a plurality of tags, where each tag isattached to an object tracked by the object tracking system,instructions for grouping identifiers of the tags within two or more tagsets based upon the location of the tag relative to a field of play,wherein tags identified within a first of the two or more tag sets arelocated on the field of play and tags identified within the other of thetwo or more tag sets are not located on the field of play, andinstructions for configuring each tag identified within the first tagset with a first ping rate and configuring tags identified within theother tags sets with a second ping rate. The first ping rate is higherthan the second ping rate.

In another embodiment, an optimizer automatically optimizes performanceof an object tracking system and includes a processor, a memory,software, stored within the memory, having machine readable instructionsthat when executed by the processor perform the steps of: receivinglocations of each of a plurality of tags, where each tag is attached toan object tracked by the object tracking system; grouping identities ofthe tags within two or more tag sets based upon the location of the tagrelative to a field of play, wherein tags identified within a first ofthe two or more tag sets are located on the field of play and tagsidentified within the other of the two or more tag sets are not locatedon the field of play; and configuring each tag identified within thefirst tag set with a first ping rate and configuring tags identifiedwithin the other tags sets with a second ping rate. The first ping rateis higher than the second ping rate.

Self-Configurable Tracking Tag

In one embodiment, an self-configurable tracking tag determines locationof an object. The tracking tag includes a processor, a transmitter fortransmitting, under control of the processor, pings at a ping rate andthat are detectable by an object tracking system, a movement sensorcoupled with the processor for sensing movement of the tracking tag, anda memory storing an algorithm having machine readable instructions thatwhen executed by the processor perform the steps of: determining, usingthe movement sensor, movement of the tag, and adjusting the ping ratebased upon the movement.

Optimizing Performance Based Upon Dynamic Tag Locations

In one embodiment, a method automatically optimizes performance of anobject tracking system having a plurality of receivers for receivingping signals from a plurality of tags, where each tag is attached to anobject tracked by the object tracking system. An optimizer receiveslocations of each of the plurality of tags and groups identifiers of thetags within two or more tag sets, where a first of the tag setsidentifies tags attached to objects involved in a situation of interest.The optimizer determines a first receiver group based upon the locationof tags identified within the first tag set and location of each of theplurality of receivers. A center of a smallest 3D polygonal shapebounding the locations of tags identified in the first tag set isdetermined and aim of an antenna of each receiver within the firstreceiver group is incrementally aimed towards the center while a numberof receiver events per second generated by the receiver for tagsidentified within the first tag set increases.

Optimizing Performance for Dynamic Environmental Changes (Filter)

In one embodiment, a method optimizes performance of an object trackingsystem. A number of receiver events per second generated by a receiverof the object tracking system is determined and the receiver iscontrolled to switch between an analog front end without a filter and ananalog front end with a filter based upon the receiver events persecond.

In another embodiment, a system optimizes performance of an objecttracking system and includes an optimizer implemented as a computer withmachine readable instructions stored on non-transitory media of thecomputer and executed by a processor of the computer to perform thesteps of: determining a number of receiver events per second generatedby a receiver of the object tracking system; and controlling, based uponthe receiver events per second, the receiver to switch between a firstanalog front end configured without a filter and a second analog frontend configured with a filter.

Generic Receiver with Multiple Analog Front Ends

In one embodiment, a reconfigurable receiver for use within an objecttracking system includes a plurality of analog front ends, eachgenerating a digital signal; a digital back end for processing one ofthe digital signals; and a digital switch for selecting, under controlof the digital back end, the one digital signal.

Optimizing Performance Based upon Dynamic Situation Changes

In one embodiment, a method optimizes performance of an object trackingsystem. An optimizer configured with the object tracking systemdetermines a bounding rectangle for locations of RF tags attached toobjects of interest. The optimizer determines a location of the boundingrectangle relative to a location of a receiver of the object trackingsystem and controls the receiver to switch from a first analog front endto a second analog front end based upon the relative location of thebounding rectangle. The first analog front end is configured with afirst range and a first scope and the second analog front end isconfigured with a second range that is different from the first rangeand a second scope that is different from the second scope.

Automatic Installation and Calibration with Robotic Vehicle

In one embodiment, an automated installation and calibration (AIC)system for an object tracking system includes a wirelessly controlledvehicle, an RF tag configured with the vehicle, and a controller for (a)receiving location data for the RF tag from the object tracking system,(b) controlling the vehicle to follow a path based upon the locationdata, and (c) adjusting orientation of at least one receiver of theobject tracking system based upon analysis of the location dataassociated with the receiver.

In another embodiment, an automated installation and calibration methodfor an object tracking system, includes the steps of: receiving locationdata generated by the object tracking system for an RF tag attached to awirelessly controlled vehicle; controlling movement of the vehicle tofollow a path based upon the location data; determining a data set oflocates from the location data based upon an area of consideration for areceiver of the object tracking system; and adjusting the orientation ofthe receiver based upon analysis of the data set.

In another embodiment, a software product has instructions, stored onnon-transitory computer-readable media, wherein the instructions, whenexecuted by a computer, perform steps for automating installation andcalibration of an object tracking system. The software product includesinstructions for receiving location data generated by the objecttracking system for an RF tag attached to a wirelessly controlledvehicle; instructions for controlling movement of the vehicle to followa path based upon the location data; instructions for determining a dataset of locates from the location data based upon an area ofconsideration for a receiver of the object tracking system; andinstructions for adjusting the orientation of the receiver based uponanalysis of the data set.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows one exemplary object tracking system with automaticoptimization, in an embodiment.

FIG. 2 shows one exemplary tag that includes a battery, circuitry, andan antenna, in an embodiment.

FIG. 3 shows the tag of FIG. 1 attached to an athlete.

FIG. 4 is a graph illustrating one exemplary ping rate of the tag ofFIG. 1.

FIG. 5 shows exemplary radial propagation of one ping from the tag ofFIG. 1.

FIG. 6 is a schematic showing one exemplary receiver for receiving theping of FIGS. 4 and 5 when transmitted by the tag of FIG. 1, in anembodiment.

FIG. 7 shows exemplary propagation of one ping from one tag to each of splurality of receivers of the system of FIG. 1.

FIG. 8 shows the tag of FIGS. 1 and 2 in further exemplary detail.

FIG. 9 is a flowchart illustrating one exemplary method for modifying acommercial UWB tag for use with the system of FIG. 1, in an embodiment.

FIGS. 10 through 12 show visual comparisons between a commerciallyavailable UWB tag and the tag of FIGS. 1 and 2 resulting from themodifications based upon the method of FIG. 9.

FIGS. 13 and 14 show exemplary attachment of two tie-wraps to the mainbody of the tag of FIGS. 1 and 2 such that attachment of the tag to anathlete's sporting equipment is simplified.

FIG. 15 shows an exemplary shoulder pad.

FIG. 16 shows the shoulder pad of FIG. 15 lifted and the tag of FIGS. 1,2, 13 and 14 attached around a hinging portion such that the tag isprotected within the shoulder pads.

FIG. 17 shows the tag of FIG. 1 positioned within a helmet worn by aplayer that provides a 360 degree radial transmission pattern when thetag is absolutely horizontal.

FIG. 18 is a top view of the tag positioned on the head of the playerillustrating propagation of a ping from the tag.

FIG. 19 shows the tag of FIG. 1 positioned on a shoulder of a player,wherein the transmission from the tag is partially obstructed by theplayer's neck and head.

FIG. 20 is a top view of each shoulder of FIG. 19 illustrating exemplaryblocking of the emitted ping by the players neck and head.

FIG. 21 shows a first scenario where the tag of FIG. 1 is mounted in thepads along the neck hole and positioned 2″ from the players head andneck.

FIG. 22 shows a second scenario where the tag of FIG. 1 is mounted inthe pads and positioned 7″ from the players head and neck.

FIGS. 23, 24, and 25 show exemplary displays illustrating player objectsthat include an arrow to indicate the direction that the player isfacing, in an embodiment.

FIG. 26 shows one exemplary tracking tag with a movement sensor for usewith the object tracking system of FIG. 1, in an embodiment.

FIG. 27 is a flowchart illustrating one exemplary method forautomatically configuring the ping rate within the tracking tag of FIG.26, in an embodiment.

FIG. 28 shows one exemplary tag manager for managing and configuring thetags of FIG. 1.

FIG. 29 shows the roster list of FIG. 28 being edited within a simpleeditor provided by the software of the tag manager.

FIG. 30 is a screen shot illustrating exemplary addition of tag IDs tothe roster list.

FIG. 31 shows the software of FIG. 28 inserting the read tag IDs intothe proper row and column of the roster list of FIG. 28

FIG. 32 shows one exemplary control screen of the tag manager of FIG. 28for configuring all tags used for a specific team.

FIG. 33 shows one exemplary status screen that is selected by clickingon the status button of the control screen of FIG. 32.

FIG. 34 is a flowchart illustrating one exemplary method for continuousaccuracy monitoring, in an embodiment.

FIG. 35 shows the optimizer of FIG.1 in further exemplary detail, andillustrating tag set management functionality of the optimizer, in anembodiment.

FIG. 36 shows one exemplary scenario where two American football teams(Team A and Team B) are setting up for a next play in an Americanfootball game.

FIG. 37 is a flowchart illustrating one exemplary method for automaticoptimization of the object tracking system of FIG. 1 based upon groupingof tags within tag sets, in an embodiment.

FIG. 38 shows an exemplary visual representation of tags groupedaccording to determined location within the operational area of FIG. 1and perimeter of the field of play.

FIG. 39 shows exemplary sub-grouping of tags within the first tag set ofFIG. 35 into sub-tag sets.

FIG. 40 is a flowchart illustrating one exemplary method forsub-grouping of tag IDs within a high priority tag set into first,second, and third sub-tag sets.

FIG. 41 shows one exemplary short yardage formation in an Americanfootball game.

FIG. 42 shows one exemplary passing formation in an American footballgame.

FIG. 43 shows the optimizer of FIG. 1 illustrating exemplary detail forcontrolling gain of the receivers.

FIG. 44 shows the system of FIG. 1 configured with twelve receivers, inan embodiment.

FIG. 45 is a flowchart illustrating one exemplary method for automaticoptimization of the object tracking system of FIG. 44 by automaticallyadjusting gain of all receivers based upon average receiver events persecond within the system, in an embodiment.

FIG. 46 shows the tag data of FIG. 43 in further exemplary detail.

FIG. 47 shows exemplary tag set boundaries that bound tags based uponthe tag sets of FIGS. 38, 41 and 42.

FIGS. 48, 49, 50, 51, and 52 collectively show a flowchart illustratingone exemplary method for automatic optimization of the object trackingsystem of FIG. 1 by controlling gain of the receivers based uponreceiver events associated with the highest priority tag set of FIG. 35,in an embodiment.

FIG. 53 shows exemplary detail of one receiver of FIG. 1, in anembodiment.

FIG. 54 shows a graph illustrating one exemplary response curve of an“off-the-shelf” receiver with unity gain at ˜6.6 GHz.

FIG. 55 shows the response curve of FIG. 54, and further illustrates thedesired frequency range of 6.35-675 GHz, in an embodiment.

FIG. 56 shows exemplary components used to upgrade an “off-the-shelf”receiver to create a band-pass filter enhanced UWB receiver for usewithin a game day environment.

FIG. 57 is a flowchart illustrating one exemplary method for modifyingand improving an “off-the-shelf” receiver to create the receiver of FIG.1.

FIG. 58 shows an assembly view of the receiver of FIG. 1 and of an“off-the-shelf” receiver.

FIG. 59 shows the receiver of FIG. 1 assembled and in comparison to theassembled “off-the-shelf” receiver.

FIGS. 60 and 61 show one exemplary receiver having a receiver body andan antenna with remotely controlled pan and tilt functionality, in anembodiment.

FIGS. 62, 63, and 64 are flowcharts illustrating one exemplary methodand sub-methods for optimizing performance of the object tracking systemof FIG. 1 by automatically and dynamically adjusting one or both of panand tilt of the antennae of FIGS. 60 and 61 to improve data qualitydetermined from tags associated with a situation of interest, in anembodiment.

FIG. 65 shows one exemplary automatic object tracking system optimizerfor automatically selecting optimal receiver configuration based uponenvironmental conditions, in an embodiment.

FIG. 66 is a schematic showing a receiver of the object tracking systemof FIGS. 1 and 65 illustrating selectable different front ends, in anembodiment.

FIGS. 67-69 show exemplary scope and range characteristics of antennaeof the receiver of FIG. 66.

FIG. 70 is a schematic showing a receiver of the object tracking systemof FIGS. 1 and 65 illustrating selectable front ends with and without afilter, in an embodiment.

FIG. 71 is a flowchart illustrating one exemplary method for automaticobject tracking system optimization based upon environmental changes, inan embodiment.

FIGS. 72 and 73 show one exemplary receiver positioned at one end of thefield of play to illustrate selection of one analog front end of thereceiver based upon situational changes.

FIG. 74 is a flowchart illustrating one exemplary method for automaticobject tracking system optimization based upon situational changes, inan embodiment.

FIG. 75 shows the system of FIG. 1 determining locates of tags withinthe operational area, wherein the calculated locates pass through anarray of filter algorithms.

FIGS. 76 and 77 show one exemplary generic method for automaticallyadjusting post-locate filters within the processing hub of the system ofFIG. 1 based upon a locate-to-ping ratio.

FIGS. 78-81 are schematics showing one exemplary bounding boxes forthree and four receivers for each of positive and negative thresholdvalues.

FIG. 82 shows the processing hub of FIG. 1 communicatively coupled witha database, a playback tool, and an analysis tool, in an embodiment.

FIG. 83 shows one exemplary static line plot generated by a static lineplotter of the analysis tool of FIG. 82.

FIG. 84 shows one exemplary enhanced static line plot that furthercombines additional error and receiver information from the recordeddata of FIG. 82 with the plotted symbols of FIG. 83 that representdetermined locates.

FIG. 85 shows one exemplary dialog box for selecting features forinclusion within the plot of FIG. 84.

FIG. 86 shows a portion of exemplary recorded data of FIG. 82 selectedby the visual data selector within the analysis tool.

FIG. 87 shows one exemplary static line plot illustrating a verydetailed circular Test Lap data set.

FIG. 88 shows one exemplary static line plot generated by the receiverviewer and the plotter of FIG. 82 of locates to display a coverage areaof a particular receiver.

FIG. 89 shows an exemplary receiver display illustrating the receiversof FIG. 1 used to determine a location of a single tag moving within thetracking area.

FIG. 90 is a schematic showing one exemplary automated installation andcalibration (AIC) system for an object tracking system, in anembodiment.

FIG. 91 shows one exemplary predetermined gross path that the vehicle ofFIG. 90 follows under control of the controller, in an embodiment.

FIG. 92 is a flowchart illustrating one exemplary AIC method forautomated location data collection using the object tracking system, thevehicle, and the RF tag of FIG. 90, in an embodiment.

FIG. 93 shows one exemplary scenario where the vehicle of FIG. 90 istravelling between points of FIG. 91.

FIG. 94 shows one exemplary area of consideration (AOC) for the receiverof the object tracking system of FIG. 90.

FIG. 95 is a flowchart illustrating one exemplary method for creating adata set for each receiver from location data collected by the method ofFIG. 92, in an embodiment.

FIG. 96 shows one exemplary predetermined coarse path that the vehicleof FIG. 90 follows under control of the controller, in an embodiment.

FIG. 97 is a top view of one receiver and its AOC showing exemplarydistribution of involving locates between a left half and a right halfof the AOC when determining automatic pan of the receiver.

FIG. 98 is a top view of one receiver and its AOC of FIG. 94 showingexemplary distribution of involving locates between a top half and abottom half of the AOC when determining automatic tilt of the receiver.

FIG. 99 is a flowchart illustrating one exemplary method forautomatically adjusting orientation of the receivers of the objecttracking system of FIG. 90, in an embodiment.

FIG. 100 shows one exemplary predetermined “fine” path that the vehicleof FIG. 90 is controlled to follow.

FIG. 101 shows the vehicle of FIG. 90 in further exemplary detail, in anembodiment.

DETAILED DESCRIPTION OF THE EMBODIMENTS Definitions

The following terms are used herein and the accompanying definitions maybe helpful in understanding the technology described herein.

Object Tracking System: A system for real time tracking of the locationof objects within an operational area, where the determined location isdefined based upon axes relative to the operational area.

Ping: A single transmission from a single tag. For example, a single tagprogrammed with a 25 Hz ping rate generates twenty-five pings persecond. Pings may preferably be lower power transmissions.

Receiver Event: When a receiver detects a ping, it generates a receiverevent. For example, if one ping is detected by ten receivers, tenreceiver events are generated within the object tracking system.

Locate: Successful position calculation of a ping. For example, a tagtransmits a ping that is detected by some number of receivers, resultingin some number of receiver events. If the object tracking system issuccessful in calculating a position of the tag based upon thesereceiver events, then the calculated position is called a Locate.

System Bandwidth: The maximum number of receiver events the objecttracking system can handle per second.

Ping Budget: The total number of pings targeted for an environment basedupon an anticipated average number of receiver events expected per pingand a total available system bandwidth of the object tracking system.

Locate-to-Ping Ratio: The ratio of successful locates to the number ofpings.

Ping Rate Allocation System: A system providing an automated method forsetting the ping rate of tags to achieve the highest possible accuracyof locates based upon the ping budget and prioritization of the object(e.g., athlete) to which the tag is attached.

Field Perimeter: The X, Y coordinates defining a field of play (e.g., anarea of interest where location is tracked more accurately, such as anAmerican football field, a soccer pitch, a running track, and so on)using the coordinate system of the object tracking system.

Max Athlete Speed: The maximum speed at which an athlete may move in anenvironment. Typically assumed to be 10 yards/second.

Receiver Event Allocation System: An automated method for allocatingresources of the object tracking system to maximize performance basedupon priority of tracked object while remaining within bandwidthlimitations of the object tracking system.

Receiver Priority Group: Collections of receivers grouped together basedon their priority to system performance.

SBWT: System Bandwidth Target. The target operating bandwidth of theobject tracking system; typically 85% of the system bandwidth.

System Optimizer: An automated method for dynamically allocatingresources (e.g., portions of the system bandwidth) of the objecttracking system, in response to athlete behavior, event flow, andchanging environmental conditions to maintain the very best performanceof the object tracking system at all times.

Tag Set: A collection of tags sharing a common priority level within theobject tracking system.

Tag Set Boundary: Minimum boundary, shaped as a rectangle or othershape, aligned to the operational axes of the object tracking system,that contains all tags of a defined group (Tag Set).

TS1BT: Tag Set 1 Bandwidth Target. This defines the bandwidth allocatedto the highest priority tag set and is used during automatic adjustmentof receiver gain. TS1BT is typically set to 70% of SBWT (SystemBandwidth Target).

Object Tracking System Overview

An Object Tracking System determines the location of objects in adefined area (e.g., to within inches) hundreds of times per second foreach object.

FIG. 1 shows one exemplary object tracking system 100 with automaticoptimization. System 100 tracks the location of tags 101 within anoperational area 102 (i.e., a tracking environment). System 100 has sixreceivers 104, positioned at known locations around operational area102, and in communication with a processing hub 150. System 100 may havethree or more receivers without departing from the scope hereof. Tags101 are attached to objects to be tracked (e.g., athletes, balls,officials, and other equipment of interest), and thereby these tags 101move within operational area 102. Each receiver 104 is receptive toUltra-WideBand (UWB) wireless signals, called “pings” herein (see pings402 of FIGS. 4 and 5), from tags 101 and sends one receiver event 110 toprocessing hub 150 for each detected ping. Algorithms 152 withinprocessing hub 150 processes receiver events 110 and generate locatedata 120 for use by one or more applications 130 via an applicationinterface 156 configured with hub 150. Applications 130 may include agraphic display generator that generates a graphic display showingdetected locations of players on a field of play 103 (e.g., an area inwhich the activity of interest occurs, such as an American footballfield, a soccer field, an athletic running track, and so on), forexample.

FIG. 2 shows tag 101 of FIG. 1 in further exemplary detail. Tag 101includes a battery 202, circuitry 204, and an antenna 206. Each tag 101has a unique tag ID 208 for identification. FIG. 3 shows tag 101 ofFIGS. 1 and 2 attached to an object of interest (e.g. athlete). In theexample of FIG. 3, tag 101 is positioned on a shoulder 302 of an athlete300 and tag ID 208 is associated with athlete 200. FIG. 4 is a graphillustrating exemplary pings 402 from tag 101, where tag 101 isconfigured to emit pings 402 at an exemplary programmable ping rate of10 Hz. FIG. 5 shows exemplary radial propagation of ping 402 from tag101 (not to scale). Each ping 402 contains information (e.g. tag ID 208and battery level) specific to the transmitting tag 101 and, in certainembodiments, ping 402 may include information (e.g. biometric data)about the object associated with the tag. A primary function of each tag101 is to periodically generate ping 402. However, tag 101 may alsoreceive transmissions that configure properties, such as ping rate,dynamically. Tag 101 may include software 210 that includes machinereadable instructions that are executed to implement this functionalitywithin tag 101.

FIG. 6 is a schematic showing one exemplary receiver 104 of FIG. 1 forreceiving pings 402 transmitted by tag 101. Receiver 104 includes atransmit/receive antenna 602, a programmable gain stage 604, analogsignal detection electronics 606 and a communication interface 608.Analog signal detection electronics 606 operates to generate receiverevents 110 that include information received from tag 101 and a time ofdetection by receiver 104.

As shown in FIG. 1, an optimizer 160 may be communicatively coupled withprocessing hub 150 to process locate data 120 and to generateconfiguration data 170 for dynamically controlling system 100 to haveoptimal performance. For example, performance of system 100 may beoptimized as weather and other environmental conditions change during amonitored game, where changes in environmental conditions affect rangeand detectability of pings 402 by receivers 104. In another example,tags 101 are dynamically configured based upon and their location, suchas when on field of play 103 (i.e., when the athlete is activelyparticipating in a current play) as opposed to when off field of play103 (i.e., when the athlete is not involved in a current play).

Processing hub 150 includes a communication interface 154 forcommunicating with receivers 104, via communication interface 608, toreceive receiver events 110. Algorithms 152 process receiver events 110from multiple receivers 104 to locate tags 101 and generate locate data120. For example, based upon three or more receiver events 110 resultingfrom one ping 402 from one tag 101, algorithms 152 generate locate data120 to include tag ID 208 and a determined location of tag 101.Application interface 156 communicates with one or more applications130. For example, each application 130 receives locate data 120 from hub500 and may further process this information to generate displaysindicative of the location within an operation environment of objects(e.g., athletes) associated with tags 101 based upon tag ID 208.

In one embodiment, optimizer 160 is a computer with at least oneprocessor and memory containing machine readable instructions that, whenexecuted by the processor, perform the functionality of optimizer 160 asdescribed herein. In another embodiment, optimizer 160 is implementedwithin processing hub 150 and comprises machine readable instructionsstored within a memory of hub 150 and executed by a processor of hub 150to perform functionality of optimizer 160 as described herein. Optimizer160 generates configuration data 170 that configures various propertiesof object tracking system 100, such as for example ping rate of tags101, analog gain of each receiver 104, and parameters used withinalgorithms 152 of hub 150.

Basic Location Operation:

The process of locating an object associated with tag 101 begins whentag 101 generates ping 402. As shown in FIG. 5, ping 402 propagatesradially outward from antenna 206 of tag 101 toward receivers 104,positioned around the perimeter of operational area 102. Receivers 104within a transmission range of tag 101, and having a line of sight (LOS)to tag 101, receive ping 402. By “LOS”, as used herein, it is meant astraight line of wireless transmission that is not obstructed, LOS doesnot necessarily relate to visual line of sight. Signal strength of ping402 at each receiver 104 depends upon a distance between tag 101 andthat receiver 104, and whether there were any obstructions, such asplayer bodies or other objects, between the tag and the receiver (i.e.,preventing LOS). Whether, or not, receiver 104 is able to decodeinformation (e.g., tag ID 208 and other information) of ping 402 dependsupon the signal strength of ping 402 at the receiver and the gainsetting of programmable gain stage 604 of the receiver. If the signalstrength and gain setting are sufficient to allow analog signaldetection electronics 606 to decode the information within ping 402,analog signal detection electronics 606 time-stamps that information andpasses it along as receiver event 110 to processing hub 150. Whereprocessing hub 150 receives at least three receive events 110 for ping402 (i.e., at least three receivers 104 receive and decode the same ping402 based upon tag ID 208 and time stamp within each receiver event110), algorithms 152 within processing hub 150 have a sufficient numberof data points (time stamps) to attempt location of tag 101 using timedifference of arrival (TDOA) techniques, as discussed in further detailbelow.

Since ping 402 travels outward at a constant speed in all directions,the time it takes to reach each receiver 104 depends directly upon thedistance between tag 101 and that receiver. That is, ping 402 reachesreceivers 104 in order based upon the distance of each receiver from tag101. FIG. 7 shows exemplary propagation of ping 402 from tag 101(2) toeach of receivers 104(2), 104 (3), 104 (5), and 104 (6) withinoperational area 102. Concentric rings 702, 704, 706, and 708, representthe position of ping 402 at times t1, t2, t3, and t4, respectively.

In the example of FIG. 7, ping 402 reaches first receiver 104(2) (ring702) at time t1, then reaches receiver 104(3) (ring 704) at time t2,then reaches receiver 104(5) (ring 706) at time t3, and then reachesreceiver 104(6) (ring 708) at time t4. Thus, receiver 104(2) generates areceiver event 110(1) including tag ID 208 of tag 101(2) and a timestamp of t1, receiver 104(3) generates a receiver event 110(2) includingtag ID 208 of tag 101(2) and a time stamp of t2, receiver 104(5)generates a receiver event 110(3) including tag ID 208 of tag 101(2) anda time stamp of t3, and receiver 104(6) generates a receiver event110(4) including tag ID 208 of tag 101(2) and a time stamp of t4. Eachreceiver event 110 also identifies the generating receiver 410. Forexample, receiver event 110(1) includes a receiver ID 714(2) thatidentifies receiver 104(2), receiver event 110(2) includes a receiver ID714(3) that identifies receiver 104(3), receiver event 110(3) includes areceiver ID 714(5) that identifies receiver 104(5), and receiver event110(4) includes a receiver ID 714(6) that identifies receiver 104(6).Although the example of FIG. 8 shows t1, t2, t3, and t4 having differentvalues, t1, t2, t3, and t4 need not be different.

A TDOA for receiver events 110(1) and 110(2) is t2-t1; a TDOA forreceiver events 110(1) and 110(3) is t3-t1; a TDOA for receiver events110(1) and 110(4) is t4-t1; a TDOA for receiver events 110(2) and 110(3)is t3-t2; a TDOA for receiver events 110(2) and 110(4) is t4-t2; and aTDOA for receiver events 110(3) and 110(4) is t4-t3.

In one embodiment, receivers 104 are fixed at known (e.g., measuredduring installation) locations around operational area 102 such that thelocation of each receiver 104 relative to the operational area is knownto algorithms 152, allowing algorithms 152 to calculate the location oftag 101(2) relative to receivers 104, and thereby relative tooperational area 102, based upon TDOA times determined from receiverevents 110. Such algorithms are known in the art, and are therefore notdescribed in further detail herein.

A successful calculation of a location of the tag 101 by processing hub150 is called a Locate. Locate data 120 contains many such locates asdetermined for each tag 101 within operational area 102. Locates, withinlocate data 120, are made available to applications 130 in real-time(i.e., almost instantaneously). Thus, applications 130 have real-timeidentification and location information of each tag 101 and itsassociated object within operational area 102.

Not all pings 402 result in locates. During typical operation of objecttracking system 100, nearly 50% of all pings 402 generated by tags 101fail to result in a locate. There are many reasons that locates cannotbe successfully calculated. For example, where fewer than threereceivers 104 successfully decode any one ping 402, algorithms 152cannot determine a location. In another example, where three receiverevents 110 are received for one ping 402, algorithms 152 may fail toconverge on a single location and therefore fail to determine a locationof tag 101. Even when processing hub 150 fails to determine a validlocate for a particular ping 402, the processing hub still makesinformation (e.g., the reason for failing to produce a locate and thespecific receivers 104 that provided receiver events 110) about ping 402available in real-time. Although information of failed locates is notuseful in most applications 130 since it does not provide tracking data,such information is extremely useful for monitoring the behavior andhealth of system 100 during operation and for optimizing performance ofsystem 100 using optimizer 160.

Tag Modifications

FIG. 8 shows tag 101 of FIGS. 1 and 2 in further exemplary detail. Tag101 is a physical device that includes a battery 202, antenna 206, andCPU and electronics 204 that are formed of a circuit board 802 with aprocessor 804 (e.g., a microcontroller), a transceiver 806 that coupleswith antenna 206. Antenna 206, circuit board 802, and battery 202 areprotected by an open casing 821 and a potting material 822. A protectivematerial 820 (e.g., hot glue) is applied around the circuit board 802and battery 202 to prevent potting material 822 from contactingsensitive components that require an air surround.

FIG. 9 is a flowchart illustrating one exemplary method 900 formodifying a commercially available UWB tag for use with system 100.Specifically, method 900 modifies mechanical aspects of the commerciallyavailable UWB tag to reduce the overall unit size, permittingconfiguration of the tag into a wide variety of athletic equipment, andruggedizing the tag to survive the rigors of athletic competition.

In step 902, method 900 removes and discards the lower section of theplastic housing. In one example of step 902, the four screws securingthe molded plastic bottom panel of the commercial tag are removed, andthe bottom portion of the case is removed and discarded. In step 904,method 900 replaces the existing battery and battery holder with a lowerpower, low profile direct PCB mount battery. In one example of step 904,the battery is removed from the battery holder, and the battery holderis unsoldered and removed from the printed circuit board. Battery leadsare trimmed to achieve a lower profile and the new battery withintegrated leads is soldered into the previous battery position withouta battery holder.

In step 906, method 900 seals around sensitive PCB areas to avoidcontamination by potting material. In one example of step 906, hot glueis used to seal the area around the battery and the circuit board toprotect components located beneath the battery that require open air tooperate (e.g., an open air filter component). Potting material thatreaches any sensitive components will significantly affect tagtransmission performance.

In step 908, method 900 replaces the tag electronics into the uppersection of the plastic housing. In one example of step 908, antenna 206,circuit board 802, and battery 202 are positioned within casing 821.

In step 910, method 900 fills the underside of the unit with pottingcompound to hold the unit in place, seal out moisture and provide alevel of shock absorption for the tag electronics. In one example ofstep 910, potting material 822 is installed around and over battery 202to form the bottom of the tag. The level of the potting material is madeno higher than the circuit board enclosure, but covering the battery forphysical and electrical protection.

In step 912, method 900 adds tie-wraps to the final assembly to allowfor quick, easy and secure mounting with athletic equipment. In oneexample of step 912, tie-wraps are screwed to the underside of case 821to facilitate attachment of tag 101 to objects being tracked.

When complete, method 900 reduces the height of the tag by approximately28%; the commercially available tag has a height of 0.810″, and themodified tag (i.e., tag 101) has a height of 0.583″.

FIGS. 10 through 12 show visual comparisons between a commerciallyavailable UWB tag and tag 101 created by implementing method 900 of FIG.9. As shown, tag 101 is much thinner and more rugged that thecommercially available tag 1002. An American quarter 1004 is shown as asize reference.

FIGS. 13 and 14 show exemplary attachment of two tie-wraps 1302 to themain body of tag 101 such that attachment of tag 101 to an athlete'ssporting equipment is simplified.

In one example of use, tag 101 is attached to an object of interest(e.g. athlete) and programmed to emit ping 402 at a defined rate. Asshown in FIG. 5, ping 402 propagates radially outward from tag 101 andincludes information (e.g. tag ID 208 and a level of battery 202)specific to tag 101 and, in certain embodiments, may include informationabout the object it is associated with (e.g. biometric data of theathlete). Although a primary function of tag 101 is to ping, tag 101 mayalso receive wireless transmissions to allow properties, such as pingrate, to be configured dynamically.

Mounting Tags on Athletes

Tag 101, configured with tie-wraps 1302 as shown in FIGS. 13 and 14, hasa high degree of installation flexibility that allows tag 101 to bemounted in any one of a wide range of shoulder pad styles having varyingconstruction techniques. FIG. 15 shows an exemplary shoulder pad 1500for use by an athlete participating in an American Football game. Theprimary concerns when mounting tags 101 in shoulders pads include (a)player safety, (b) range of motion, (c) horizontal mounting, and (d)physical protection of the tag. To meet these concerns the followingpoints should be considered:

-   -   To protect players from injury (a), tag 101 is preferably        mounted within the shoulder pads (e.g., shoulder pad 1500)        leaving a layer of padding material between the tag and the        player's body.    -   Tag 101 is preferably mounted within the shoulder pads such that        the tag does not hinder a player's range of shoulder motion (b).    -   Tag 101 is preferably placed such that the transmission plane of        the tag is oriented as horizontal as possible (c). If tag 101 is        mounted at an angle from horizontal, then signal reception may        be compromised as the transmission would be directed toward the        ground and/or overshoot receiver 104 positioned around        operational area 102.    -   For protection of tag 101 (d), the tag is preferably mounted        within the shoulder pads (i.e., not positioned on top of the        shoulder pads). Tag 101 is also preferably mounted such that the        tag does not become the point of contact during a collision        between two players.

FIG. 16 shows shoulder pad 1500 of FIG. 15 lifted, and tag 101 attachedaround a hinging portion such that tag 101 is protected within theshoulder pad. Virtually all manufactured shoulder pads have a mountinglocation that meets these requirements to an acceptable level. With theplayer's safety and range of motion addressed and tag 101 adequatelyprotected, the focus moves to optimizing performance of tag 101.

FIG. 17 shows tag 101 positioned on top of a player's head 1702 (e.g.,configured within a helmet worn by the player) to provide a 360 degreeradial transmission pattern 1802, as shown in FIG. 18, when the tag ishorizontal. FIG. 19 shows two tags 101, each positioned on a differentshoulder of the player. The transmission of pings 402 from each tag 101is partially obstructed by the player's neck and head 2002. as shown inFIG. 20. To minimize the impact of this line of sight obstructionbetween tag 101 and receivers 104, tags 101 are placed on the shoulderas far away from the neck and head as possible while meeting theconcerns described above. This reduces transmission blocking to thegreatest extent possible.

In an American Football game example, assume a player is standing withtheir shoulders facing an end zone and tag 101 has its line of site to aline of receiver 104 that are 300′ away blocked by the players head andneck.

FIG. 21 shows a first scenario 2100 where tag 101 is mounted in the padsalong the neck hole and positioned 2″ from the players head and neck.Given the proximity of tag 101 to the player's neck and head, a wideangle (e.g., 126°) of transmission is blocked by the athlete's head andneck. At a range of 300′, the length (d) of a transmission blockage isapproximately 1176 feet, thus eliminating an entire side of operatingarea 102 and any receivers 104 positioned along that side.

FIG. 22 shows a second scenario 2200 where tag 101 is mounted in thepads (e.g., as shown in FIG. 16) and positioned 7″ from the players headand neck. As shown in FIG. 21, this mounting position for tag 101greatly reduces the portion of the transmission blocked by the neck andhead by about 50% to approximately 60°. In this example, at a range of300′, the length (d) of the transmission blockage is reduced toapproximately 345 feet, thereby allowing a much greater line of siteaccess for receivers 104 to receive pings 402 from tag 101.

Shoulder Centerline Mounting

Consideration is also given to how an athlete moves while playing theirsport. Continuing with the American Football example, a player may be ina bent forward position while lining up for a play to start, and may bebent slightly forward while running during the play. In most footballsituations, other than walking around between plays, a player has somesort of bend in their hips, with his torso tilted forward. Therefore, toachieve optimum tag transmission the tag is mounted as far back from thecenterline of the shoulders as possible while meeting the other concernsof positioning described above. This positions tag 101 substantiallyhorizontal during game play and thereby optimizes propagation of pings402 from the tag.

Benefits of Mounting Tags on Shoulders

A. Elimination of Single Point of Failure

Mounting two tags 101, each within a different shoulder pad of the sameplayer, has certain advantages over using a single tag mounted in theplayer's helmet. For example, if a player is fitted with a single tag(e.g., configured in the helmet as shown in FIGS. 17 and 18) fails atany time during game play, positional information of that player wouldbe lost for the remainder of the game. Such information loss for theplayer over an extended time during game play may misrepresent playerparticipation and within tracking system 100, automatic play start andstop detection malfunctions, and play type detection malfunctions mayoccur. By placing two tags 101 in both left and right shoulder pads of asingle player, redundant player position data is achieved, thuseliminating a single point of failure within tracking system 100. InAmerican Football there are also many occurrences during play where asingle tag 101 on one shoulder of a player may have no line of sight toa sufficient number of receivers 104 (a minimum of three receiver events110 for a single ping 402 is required to determine a location) tocalculate positional data. During these occurrences the opposingshoulder tag 101 is likely to still have line of sight to at least threereceivers 104 resulting in continued determination of positional datafor the tracked player.

B. Centerline Constant

When both left shoulder and right shoulder tags 101 are functioningnormally, and have adequate line of site to receivers 104, theirpositional data may be combined to form a single player object. Thissingle player object combines positional data from both tags to create acenter line representation of the player's position. This center linecalculated position provides a more accurate representation of thecenter of a player's position on the playing field.

C. Rotational Information

Using the relative positional data from two tags 101 positioned on theleft and right shoulders of a player, prior to creating the singleplayer object as described above, allows system 100 to determine adirection (rotation) that the player is facing. FIGS. 23, 24, and 25show exemplary displays 2300, 2400, and 2500, respectively, illustratingplayer objects 2302 that include an arrow to indicate the direction thatthe player is facing. Rotational data is a useful addition to locatedata 120, particularly for a coaching application 130. Further, theinclusion of rotational data greatly eases the task of creating avatarrepresentations from game data sets created by recording locate data 120(e.g., within an application 130) during a game.

AcceloTag

As discussed in further detail below, object tracking system 100 has abandwidth limit for the number of receiver events 110 (and thereby anumber of pings 402) that it may continuously handle. To avoidsaturation of system 100, tags 101 may be configured with a ping rate(i.e., a rate at which tag 101 generates pings 402, such as ten pingsper second for example) based upon the (a) the bandwidth limit of system100 and (b) the expected activity of each object (e.g., aplayer/athlete) to which the tags are configured. Objects that areexpected to have greater movement and/or activity are of most interestto application 130, and ultimately viewers thereof, connected to system100. Thus, tracking tags attached to these objects are typicallyconfigured with a higher ping rate such that system 100 determines thelocation of these objects more frequently. Where the expected activityof the object is accurately predicted, this method of operation workswell. However, where the activity of the object does not occur asexpected, the allocated ping rates may result in non-optimal tracking bysystem 100. For example, where a player is expected to have a high levelof activity, a high ping rate is allocated to one or more tags 101attached to that player. When the player does not exhibit the expectedactivity, bandwidth of the tracking system is wasted. Where anotherplayer is not expected to have a high activity level, tags associatedwith that player are configured with a low ping rate. However, if thatplayer does exhibit a high level of activity, system 100 may not trackthat player with the accuracy and reliability commensurate with theactivity due to the lower ping rate.

FIG. 26 shows one exemplary tag 2601 that is similar to tag 101 of FIGS.1, 2 and 8, including a battery 2602, a microcontroller 2604, an antenna2606, and an RF circuit 2616, but is further configured with a movementsensor 2650. Microcontroller 2604 includes a processor 2620 and memory2622 shown storing a ping rate 2626 and an algorithm 2628. RF circuit2616 is for example a transceiver for receiving and transmitting radiosignals via antenna 2606. For example, RF circuit 2616, under control ofmicrocontroller 2604, generates pings (e.g., ping 402, FIGS. 4 and 5),based upon ping rate 2626, that are detected by receivers 104 of system100. Movement sensor 2650 is for example one or more of anaccelerometer, a GPS receiver, and so on, that operates to determinemovement of tag 2601. In one embodiment, movement sensor 2650 includesthree orthogonally orientated accelerometers that cooperate to detectacceleration of tag 2601 in three dimensions.

Algorithm 2628 contains machine readable instructions (i.e., software)that are executed by processor 2620 to detect movement of tag 2601 usingmovement sensor 2650. Algorithm 2628 thereby detects movement and/oractivity of an athlete configured with tag 2601. Algorithm 2628 mayutilize acceleration information from movement sensor 2650 to determineactivity as a speed of tracking tag 2601 in a horizontal plane. Basedupon this determined activity, algorithm 2628 may increase and/ordecrease ping rate 2626, thereby adjusting the rate at which pings aretransmitted from tracking tag 2601. In one example of operation, whenalgorithm 2628 detects that tracking tag 2601 is stationary or movingvery little, algorithm 2628 reduces the value of ping rate 2626, therebyreducing the rate at which pings are transmitted from tracking tag 2601.In another example of operation, when algorithm 2628 detects thatdetermined activity (e.g., speed) of tracking tag 2601 has increasedabove a predefined threshold, algorithm 2628 increases the value of pingrate 2626, thereby increasing the rate at which pings are transmittedfrom tracking tag 2601.

Tracking tag 2601 is optionally configured (e.g., predefined withinmemory 2622 or automatically set by system 100) with ping rate limits,such as one or both of a maximum ping rate 2630 and a minimum ping rate2632 that define a maximum and a minimum rate, respectively, that tag2601 may transmit pings. For example, maximum ping rate 2630 and/orminimum ping rate 2632 may be set by the object tracking system basedupon one or more of bandwidth limitations, a number of active trackingtags 2601, and a type of expected activity (e.g., sport and eventtypes). When configured with one or both ping rate limits, algorithm2628 operates to adjust ping rate 2626 between minimum ping rate 2632and maximum ping rate 2630. Thus, automatic optimization of objecttracking system 100, as described above, may be used in combination withautomatic ping rate adjustment of tracking tag 2601.

Use of algorithm 2628 and movement sensor 2650 within tracking tag 2601increases reliability of system 100 to track objects configured with tag2601 as compared to tracking of objects configured with tag 101,particularly when objects becomes more active than expected. In anAmerican football example, a lineman is not expected to move veryquickly and a ping rate of tags 2601 associated with the lineman isconfigured with a relatively low ping rate. However, if the linemanunexpectedly receives the ball and runs towards the end zone, ping rate2626 of tracking tag 2601 is automatically increased by algorithm 2628,based upon activity detected by movement sensor 2650, thereby enablingthe tracking system to determine location (i.e., locates) for thelineman at an increased rate commensurate with the actual motion of thelineman.

In one embodiment, algorithm 2628 compares detected motion from movementsensor 2650 to a predefined threshold 2634, wherein algorithm 2628increases ping rate 2626 when detected motion is greater than predefinedthreshold 2634 (e.g., until ping rate 2626 reaches maximum ping rate2630), and wherein algorithm 2628 decreases ping rate 2626 (e.g., untilping rate 2626 reaches a minimum ping rate 2632) when detected motion isless than predefined threshold 2634.

Algorithm 2628 may be configured specifically to the type of activity(e.g., type of sporting event) being tracked. For example, algorithm2628 may be configured to determine ping rate 2626 using a specificformula and detected motion, where the specific formula calculates pingrate 2626 proportional to the detected motion given the limitations ofthe type of activity. Examples of formulae that determine and/or changeping rate 2626 relative to sensed motion from movement sensor 2650 mayinclude one or more of a simple linear relationship, a thresholdedrelationship, a weighted relationship, and a non-linear relationship.

In one example of operation, microcontroller 2604 runs algorithm 2628 toset ping rate 2626 to a default or baseline rate that is predeterminedby designers of the system and/or dynamically by system 100. During atracked event, microcontroller 2604 executes algorithm 2628 to readmovement sensor 2650 (e.g., by either sampling analog outputs or readingdigital outputs of movement sensor 2650) and to adjust or change pingrate 2626 to control the rate at which pings are transmitted fromtracking tag 2601.

Since algorithm 2628 automatically controls ping rate 2626 in real timebased upon actual activity of the object being tracked (as opposed topredicted activity), bandwidth of the tracking system is automaticallyallocated to tags associated with the active objects. Least activeobjects automatically have a lower ping rate as compared to more activeobjects. For example, during a play in an American football game,players that are most involved in manipulating (e.g., throwing, catchingand running with) the football, both for offensive and defensive teams,are the ones moving and changing directions at the highest rate. Playersthat have a brief interaction with the play may stop moving or slow downsignificantly. Thus, each tracking tag 2601 automatically configuresitself such that players with the highest level of motion and change ofdirection have the highest ping rates and lesser active players have acorrespondingly lower ping rate. The tracking system is thereforeautomatically optimized to track the more active (e.g., faster) playersand is less burdened by tracking of slower players; equivocal locationcalculations are not required for all players. Further, since thistechnique is automatic and autonomous within each tag, no additionalreconfiguration or reconfiguration overhead occurs within receivers orlocation processors of system 100.

In an alternate embodiment, within each tracking tag 2601, algorithm2628 determines activity of tracking tag 2601 based upon movement sensor2650 and sends (e.g., by including a value indicative of the activityand/or acceleration within each ping transmitted from tag 2601) anindication of the activity to the object tracking system. The objecttracking system may utilize an algorithm to determine an optimal pingrate for each tracking tag 2601, and then automatically set (e.g.,wirelessly) ping rate 2626 of each tracking tag 2601 individually and/orcollectively (e.g., in groups). In this embodiment, the object trackingsystem advantageously learns current activity of all tracking tags 2600and may determine each individual ping rate based upon activity of alltracking tags and the system bandwidth.

In yet another embodiment, memory 2622 may store a dynamic flag 2636,configured (e.g., set wirelessly) by the object tracking system 100,that determines whether algorithm 2628 automatically, or not, changesping rate 2626 based upon determined activity. For example, the objecttracking system may set dynamic flag 2636 to “false” for tags 2601associated with players not currently participating on the field ofplay, wherein ping rate 2626 remains at a low rate even if the player isactively warming up for example. Object tracking system 100 sets dynamicflag 2636 to “true” for players that are actively participating on fieldof play 103.

FIG. 27 is a flowchart illustrating one exemplary method 2700 forautomatically configuring ping rate 2626 within tracking tag 2601.Method 2700 is for example implemented within algorithm 2628 of trackingtag 2601.

In step 2702, method 2700 reads the movement sensor. In one example ofstep 2702, under control of algorithm 2628, processor 2620 readsmovement sensor 2650. In step 2704, method 2700 determines activitybased upon the information read from the movement sensor. In one exampleof step 2704, algorithm 2628 determines activity based upon informationread from movement sensor 2650. In step 2706, method 2700 calculatesping rate based upon the activity determined in step 2704. In oneexample of step 2706, algorithm 2628 calculates ping rate 2726, basedupon, using a linear formula with determined activity, maximum ping rate2630 and minimum ping rate 2632. Steps 2702 through 2706 repeat tocontinuously update ping rate 2626 based upon activity determined frommovement sensor 2650.

Player Tag Management System

For useful operation of system 100 of FIG. 1, configuration as to whichtag(s) 101 is installed on which tracked object (e.g., athlete) iscritical. Where multiple tags are installed on a single object, it isalso important that system 100 knows the location (e.g. left shouldervs. right shoulder of the athlete) of each tag on the object. Theassignment of specific tags 101 to athletes, and the configuration ofthose tags, is technically straightforward for an individual tag.However, in the “game day” environment, managing a large number (i.e.,hundreds) of tags in a relatively short period before the start of anevent is challenging.

FIG. 28 shows one exemplary tag manager 2802 for managing andconfiguring tags 101. Tag manager 2802 is a computer that includes awireless transceiver 2804 for communicating with tag 101, a memory 2806,and a processor 2808. Tag manager 2802 includes software 2810 that hasmachine readable instructions stored within memory 2806 and executed byprocessor 2808 to provide functionality of tag manager 2802 as describedbelow. In one embodiment, tag manager 2802 is a tablet PC and software2810 is a standard Windows program.

In the following example, two tags 101 are installed in the left andright shoulder pads of an American football player. However, thefollowing procedure process applies to any number of sports where one ormore tags are to be installed on each athlete.

As described above, each tag 101 includes unique tag ID 208. Tag 101also has other one or more parameters 2801 that are configurable.Parameters may control features including: on/off, ping rate, andexternal I/O interface. Tag manager 2802 is also used to configuremultiple tags 101 collectively, such as setting parameters 2801 for tagsattached to all athletes in a locker room before and/or after a sportingevent. Transceiver 2804 has low sensitivity and wireless range such thatcommunication with tag 101 only occurs when tag is in close proximity totag manager 2806 thus limiting the possibility of inadvertentlyprogramming tags installed in equipment of other players.

A typical sporting event involves hundreds of tags, and without tagmanager 2802, alphanumeric tag ID 208 of each tag 101 would need to bemanually entered into a tag assignment table together withidentification of the athlete to which the tag is associated. Typicallythese type of tag ID's are long strings of seemingly random alphanumericcharacters (e.g. 8 digit hexadecimal numbers). Entering hundreds ofthese numbers manually almost inevitably leads to human error. With sucha manual method, the first sign of a data entry error is typically whenan athlete later walks out on the field and is his tags cannot be read.At that point, it is usually too late to find and correct the errorresulting in data for that tag ID which is missing or, even worse,inaccurate for the entire event.

Tag manager 2802 includes tag list 2814 (e.g., a file stored in memory2806 and/or within a database 2812) that includes a list of tag IDs 208for a particular collection of tags 101. Tag manager 2802 builds taglist 2814 by automatically reading tag ID 208 from each tag 101 withinthe collection (e.g., say a bag or a box of tags). Continuing with theAmerican football example, to install two tags in each of 50 pairs ofshoulder pads, the first step would be to create two tag lists 2814(1),2814(2), each having 50 tags, one list for the left shoulders and onefor the right shoulders, respectively.

Tag manager 2802 also includes a roster list 2816 (e.g., a file storedwithin memory 2806 and/or within database 2812) that containsinformation about each athlete on a single team. For each player, at aminimum, roster list 2816 contains a player number or name and a tag ID208 for each tag that installed on or associated with the athlete, aswell as the position of the tag on the athlete (e.g. left shoulder).Where tag 101 supports configurable parameters 2801 (e.g. ping rate)then those settings would also be stored in roster list 2816.

Tag manager 2802 creates and manages roster list 2816, which is alsoused by applications 108 of system 100 where each tag ID 208 isassociated with a player's name or number.

Roster list 2816 may be created prior to tag installation, therebyreducing the workload of the person installing the tags. For example,the player numbers, names, and desired tag speeds are usually knownahead of time. FIG. 29 shows roster list 2816 being edited within asimple editor provided by software 2810 of tag manager 2802.

Having prepared two bags of tags 101 and their associated tag lists2814(1) and 2814(2), tags 101 may be physically installed in all theshoulder bags, as described above. During installation, no attentionneed be paid to the tag ID of individual tags. The process just involvesinstalling any tag from the Left Shoulder bag in all of the leftshoulders and any tag from the Right Shoulder bag in the rightshoulders.

As each set of pads is completed, or when installation of tags in allpads is complete, tag manager 2802 is used to automatically add the tagIDs 208 to roster list 2816. FIG. 30 is a screen shot 3000 illustratingexemplary addition of tag IDs 208 to roster list 2816. A user of tagmanager 2802 clicks in the “TagID” column for a specific set of shoulderpads that have already had their tags installed. The user then aims thetransceiver 2804 at that pair of pads and clicks an “Add Tags” button3002. Upon selection of “Add Tag” button 3002, tag manager 2802 readsall tags within wireless range of transceiver 2804. Software 2810 thenverifies that only two tag IDs have been read. If not, software promptsthe user to try again. Software 2810 then verifies that one of the readtag IDs is from the left tag list 2814(1) and that the other tag ID isfrom the right tag list 2814(2). Then software 2810 inserts the read tagIDs into the proper row and column of roster list 2816, as shown in FIG.31.

In general, tags 101 are installed in the shoulder pads sometime wellbefore the first event in which they are to be used. On the day of anevent, all tags 101 are programmed. At a minimum, each tag 101 isactivated (i.e., turned on), and optionally other parameters areconfigured (ping rate, external I/O, etc.). Tag manager 2802 provides afast and reliable method of configuring all of the tags associated witha single team, even in the hectic environment of a pre-game locker room.

FIG. 32 shows one exemplary control screen 3200 of tag manager 2802 forconfiguring all tags 101 used for a specific team. Pull-down list 3202selects a particular roster list 2816, pull-down list 3204 selects aparticular configuration for parameters 2801 (e.g., turn the tags on andconfigure them, or turn them off), and “Program” button 3206 activatesthe programming of the tags listed within the selected roster file 2816.Once button 3206 is selected, tag manager 2802 continuously scans fortags 101 within range of transceiver 2804. For each tag 101 with tag ID208 listed within roster list 2816, tag manager 2802 turns it on andconfigures it as specified in the roster list.

FIG. 33 shows one exemplary status screen 3300 that is selected byclicking on status button 3208 of control screen 3200. Status screen3300 shows roster list 2816 where, as each individual tag is detectedand programmed, the tag ID is highlighted in green 3302 or yellow 3304to indicate that it is ready. Yellow 3304 indicates that the batterylevel of the tag is low. Green 3302 indicates that the battery of thetag is OK. As tag manager 2802 moves around the locker room, more andmore tags 101 are automatically programmed and marked as “ready”. Whenthe last tag is programmed, tag manager 2802 displays a message sayingthat the entire roster's tags have been successfully programmed.

If you get to the end of the locker room and some tags have beenaccidentally missed, it's a very simple matter to scroll through rosterlist 2816 to identify which tag(s) have not been programmed (i.e., nothighlighted in green or yellow). The system will tell you for examplethat a left shoulder tag of Player #12 (Player 3) has not yet beenprogrammed.

Continuous Accuracy Measurement:

In system 100 of FIG. 1, location accuracy is extremely important and itis absolutely crucial where system 100 is used at high profile sportingevents. Where system 100 is operating without interference, locate data120 defining the location of each tag 101 is regularly reported (manytimes a second) and is reliably and consistently accurate. However,various anomalous conditions may arise that degrade the accuracy ofsystem 100.

System 100 may include a continuous accuracy monitoring application130(2) that provides a continuous measure of location accuracy withinsystem 100. Where application 130(2) determines that accuracy of system100 is affected beyond a pre-set threshold, an operator is immediatelynotified and may take appropriate corrective action.

System 100 uses the precise physical location (X,Y,Z) of each receiver104, as well as the location (e.g., X, Y, Z position relative toreceivers 104) of one or more test tags 101. The calibration andaccuracy of system 100 depends upon knowing these precise locations. Theposition measurements of all other tags 101 by system 100 are indirectlybased on these test tags. Once installed, system 100 is robust andreliable by design, but there are various events and situations that maycompromise accuracy of the position measurements for all tags by thesystem. Distinct from catastrophic system failures, compromised locationaccuracy may easily go unnoticed for an extended period, resulting in adata set for the event which, at best, is suspect or, at worst, iscompletely unusable.

Application 130(2) constantly monitors the system's overall accuracy ofmeasurement and immediately alerts an operator of system 100 whenmeasured accuracy is outside a pre-set threshold. When system 100 isinstalled, some number of test tags are physically mounted at fixedlocations within or around operating area 102 (e.g., within the sportsfacility). In one embodiment, test tags 101 are permanently mounted witha continuous power supply in place of battery 202. System 100 mayinclude two or three test tags 101 on each side of operating area 102,spaced at roughly even intervals. When system 100 is installed, theprecise (X,Y,Z) positions of these test tags are measured (e.g., by alaser measurement device) to the same level of exactness as thedetermined location of receivers 104.

When these test tags are installed there are a set of conditions thatmust be met for the continuous accuracy monitoring system to work:

-   -   Each test tag 101 is triangulated upon using a subset of all        receivers 104 of system 100.    -   Each receiver 104 is involved in the triangulation of at least        one test tag 101.

Once system 100 is installed, the position of each test tag 101, asdetermined by system 100, is recorded. Ideally, the position of eachtest tag 101 determined by system 100 exactly matches the laser measuredposition of each test tag 101. In reality, however, there is always asmall discrepancy; the accepted error range is +/−6 inches for example.The discrepancy is recorded upon the initial triangulation of each testtag. During the initial installation the only significance to thoseerror measurements is that they should be less than the maximum allowedsystem error. If not, it indicates a problem with the installation thatmust be fixed before proceeding.

Once installation is complete, continuous accuracy monitoringapplication 130(2) continuously reads the reported position of each testtag 101. Each reported position may vary slightly due to noise withinsystem 100. System 100 averages the incoming position measurements foreach test tag 101 to reduce the system noise. Application 130(2) thencalculates the error using the averaged position measurement and thelaser measured position of the test tag 101. System 100 then comparesthis measured error to the acceptable error (e.g., +/−6 inches) for thattag. If the difference between these two errors is greater than thepre-determined threshold, or if the measured error itself is greaterthan the maximum acceptable error, then application 130(2) generates analert condition.

The alert condition consists of popping up a message on the operator'sPC, logging the condition in a log file and broadcasting the event onthe PC's network to all connected system application programs that asystem operator would use.

One of the advantages of the design of system 100, particularly asdeployed for sporting venues, is that there is a great deal ofredundancy built in. Even if many important individual components fail,system 100 continues to work with a reasonable level of smoothlydecreased accuracy or throughput. While system 100 is still usable inthat case, it is still very important to be aware of the fault. Errorconditions that the Continuous Accuracy monitoring application 130(2)may detect include:

Hardware failure of a receiver 104

Hardware failure of a cable to receiver 104

Hardware failure of an Ethernet port to receiver 104

Hardware failure of a test tag 101

Physical blockage of a test tag 101

Physical obstructions between a receiver 104 and the field

Very heavy rain

Application 130(2) may not determine the cause of any problem, only thatsomething is causing a measurable drop in the accuracy of system 100. Itis up to the operator to then determine the specific cause of theproblem using all the diagnostic tools at their disposal.

FIG. 34 is a flowchart illustrating one exemplary method 3400 forcontinuous accuracy monitoring, in an embodiment. Method 3400 is forexample implemented within continuous accuracy monitoring application130(2). In an alternate embodiment, method 3400 is implemented withinprocessing hub 150.

In step 3402, method 3400 extracts test tag locates from a current dataset. In one example of step 3402, locations of test tags 101 resultingfrom receiver events 110 of pings 402 emitted by the test tags areextracted from locate data 120. In step 3404, method 3400 compares alltest tag locations to their calibration value. In one example of step3404, determined locations of test tags 101 are compared to test tagcalibration factors input in step 3406.

Step 3408 is a decision. If, in step 3408, method 3400 determines thatthe determined location of all test tags are within system tolerances,method 3400 continues with step 3414 and terminates until invoked again;otherwise method 3400 continues with step 3410. In step 3410, method3400 generates a system alert to all applications. In one example ofstep 3410, processing hub 150 generates and sends an alert toapplications 130 to indicate the determined location error. In step3412, method 3400 issues an operator warning indicating that systemaccuracy is compromised. In one example of step 3412, processing hub 150issues an operator warning to one or more operators of system 100.

Method 3400 then terminates. Method 3400 is invoked periodically orcontinuously to evaluate performance of system 100.

Uses of Continuous Accuracy Monitoring:

When an operator arrives at a sports facility and activates system 100,without any additional equipment, the operator may immediately verifythat system 100 is working correctly and that nothing significant haschanged since the last time it was used. If a piece of equipment failssuddenly (e.g. a cable is cut) continuous accuracy monitoringapplication 130(2) will provide an immediate warning that something hasgone wrong. In some cases, continuous accuracy monitoring application130(2) notifies the operator of conditions that cannot or will not beimmediately corrected. Continuous accuracy monitoring application 130(2)may also indicate when the condition is causing a slight degradation inthe quality of locate data 120 but is still sufficiently accurate tocontinue use of system 100. In those cases, it is still useful to benotified so that any collected data may automatically or manually beannotated to indicate that the quality is reduced. This may be veryhelpful when later analyzing collected locate data 120.

Automatic Optimization of the Object Tracking System

Continuing with the example of FIG. 1, optimizer 160 dynamicallyallocates bandwidth and resources of system 100 in response to athletebehavior, event flow, and changing environmental conditions toautomatically maintain optimal performance of object tracking system100.

Optimizer 160 utilizes a three tiered approach for automatically, anddynamically, adjusting object tracking system 100 such that the bulk ofreceiver events 110 are received, and locates are determined, for tagsassociated with objects having the most value, such as tags attached toactive athletes on field of play 103. Optimizer 160 calculates alocate-to-ping ratio of system 100 based upon pings 402 generated bytags 101 and resulting locates within locate data 120. Thelocate-to-ping ratio is for example a percentage value determined bydividing the number of generated locates by the number of pings 402expected during a defined period. Optimizer 160 operates to maintain thelocate-to-ping ratio at a desired value (e.g., fifty-five percent) suchthat the bandwidth of system 100 is not saturated. Optimizer 160 mayalso calculate a locate-to-ping ratio (see locate-to-ping ratio 4340 ofFIG. 43) for one or more specific tags 101 and operate to simultaneouslyincrease the locate-to-ping ratio for tags attached to athletes ofparticular interest, while keeping the system bandwidth of system 100 ata safe margin below saturation.

TABLE 1 Example Parameters Parameters Value Type Target (Locations) 1320Locates/sec Locate-to-ping ratio 55% % of Good Pings from total TotalPing Budget 2400 Total # of pings to work with Number of Players 96 48Players per team Players on Field 22 11 Players from each team Number ofLinemen on Field 10 5 Linemen on field/team Number of mobile players onfield 8 4 mobile players on field/team Number of skill players on field4 2 skill players on field/team Max Player Speed 10 yards/sec

Ping Rate Allocation

In many sports (e.g. American football) tracked by system 100, a largenumber of tagged athletes are located within operational area 102,although a far smaller number of these athletes are of specific interestat any given time. Table 1 Example Parameters shows exemplaryconfiguration parameters of system 100 for an American football eventwhere ninety-six tagged players are involved in the event. In thisexample, the bandwidth of system 100 is limited to handle two-thousandfour-hundred pings per second. Assuming that each of the ninety-sixplayer has one tag 101 that is configured to a uniform ping rate, andconfigured to exploit the available bandwidth of system 100, then themaximum ping rate that each tag may be configured to is twenty-fivepings per second (2400/96=25). Considering a Max Athlete Speed of 10yards/sec and locate-to-ping ratio of 55%, the potential distancetraveled by a player between valid locates is 26.2 inches (See Table 2Uniform Distribution Example).

TABLE 2 Uniform Distribution Example Parameters Value Type Number ofTags 96 Ping rate per Tag 25 Pings used from total ping budget 2400Located pings/tag/sec 14 Time between locates 0.07 Seconds Potentialdistance traveled (yds) 0.73 Yards Potential distance traveled (inches)26.2 Inches Remaining ping budget 0

In the example above, the total ping budget is consumed; however,performance of system 100 in this configuration is not optimal. While itis important to know if players are on the side lines, it is notnecessarily important to know precisely where they are on the sidelineat any given instant. However, it is very important to know where theplayers currently playing on the field are as accurately as possible.

FIG. 35 shows optimizer 160 of FIG. 1 in further exemplary detail,illustrating tag set management functionality within data 164. Optimizer160 includes a ping rate allocator 3502 that is implemented withinsoftware 162 as machine readable instructions that are loaded andexecuted within optimizer 160.

FIG. 36 shows one exemplary scenario 3600 where two American footballteams (Team A and Team B) are setting up for a next play in an Americanfootball game. Each player of each team is equipped with one tag 101such that system 100 of FIG. 1 may determine and track a location ofeach player. In scenario 3600, a tracked location of each player of teamA is represented by an “X”, and a tracked location of each player ofteam B is represented by an “O”. There are ninety-six players in total(forty-eight on each team). Thirty-seven players of team A are on onesideline of field of play 103, thirty-seven players of team B are on theopposite sideline of field of play 103, and eleven players of each teamare on field of play 103 preparing to play.

First, ping rate allocator 3502 groups identifiers (e.g., tag ID 208) oftags 101 within tag sets 3512 (including sub-tag sets where used) basedupon a reported location of each tag 101 from processing hub 150,knowledge of the perimeter of field of play 103, and optionally the teamassignment of each tag 101. Then, ping rate allocator 3502 configureseach tag 101, using transmitter 180 for example, with a ping rate basedupon which tag set 3512 its identifier is included within. For example,tags 101 identified within tag set 3512(1) are configured with a higherping rate than tags identified within tag set 3512(2). Ping rateallocator 3502 determines the ping rates for each tag set 3512 basedupon control parameters 3514 that include information such as: a pingbudget that defines the maximum number of pings per second that system100 handles, and an off field ping rate that defines a ping rate fortags 101 of objects not located on field of play 103.

In one example of operation, ping rate allocator 3502 includes tag IDs208 of tags 101 located on field of play 103 within tag set 3512(1),includes tag IDs 208 of tags 101 associated with players of team A thatare not on field of play 103 within tag set 3512(2) and includes tag IDs208 of tags 101 associated with players of team B that are not on fieldof play 103 within tag set 3512(3). Ping rate allocator 3502 thendetermines and assigns a ping rate to each tag 101 based upon knowledgeof the ping budget of system 100 and tag set 3512 in which the tagidentifier is grouped. In this example, ping rate allocator 3502 setstags identified within tag set 3512(1) (the higher priority tag set) tooperate with a faster ping rate than tags identified within tag sets3512(2) and tag set 3512(3) (the lower priority tag sets). Ping rateallocator 3502 may operate with more or fewer tag sets 3512 withoutdeparting from the scope hereof. For example, more tag sets may be usedwhere different sports are being tracked by system 100. Tags configuredwith a faster ping rate produce higher location accuracy as compared totags configured with a slower ping rate.

FIG. 37 is a flowchart illustrating one exemplary method 3700 forautomatic optimization of object tracking system 100 of FIG. 1, basedupon grouping of tags 101 within tag sets 3512. Method 3700 is forexample implemented within ping rate allocator 3502 of FIG. 35. In step3702, method 3700 identifies tags and determines the field perimeter. Inone example of step 3702, ping rate allocator 3502 identifies tags 101active within system 100 and determines, from measured and/or predefinedparameters 3514 stored within optimizer 160, details of a perimeter offield of play 103. In step 3704, method 3700 acquires current locationof each tag. In one example of step 3704, ping rate allocator 3502receives locate data 120 from processing hub 150. Steps 3706 through3718 form a loop that is iterated for each tag identified in step 3702.

Step 3708 is a decision. If, in step 3708, method 3700 determines thatthe determined location of the current tag is within the determinedperimeter, method 3700 continues with step 3710; otherwise method 3700continues with step 3712. In step 3710, method 3700 assigns the currenttag to a high priority tag set. In one example of step 3710, ping rateallocator 3502 adds tag ID 208 of tag 101 to tag set 3512(1). Method3700 continues with step 3718.

Step 3712 is a decision. If, in step 3712, method 3700 determines thatthe current tag is on a player of team A, method 3700 continues withstep 3714; otherwise method 3700 continues with step 3716. In oneexample of step 3712, ping rate allocator 3502 utilizes tag ID 208 ofthe current tag 101 to lookup associated information, within a databasedefining tag assignments for example, defining the player that thecurrent tag 101 is assigned to. In step 3714, method 3700 adds thecurrent tag to a low priority tag set for team A. In one example of step3714, ping rate allocator 3502 adds tag ID 208 of current tag 101 to tagset 3512(2). Method 3700 continues with step 3718. In step 3716, method3700 assigns the current tag to a low priority tag set for team B. Inone example of step 3716, ping rate allocator 3502 adds tag ID 208 ofcurrent tag 101 to tag set 3512(3).

In step 3718, method 3700 returns to step 3706 to repeat steps 3708through 3718 for subsequently selected tags. Once all tags areprocessed, method 3700 continues with step 3720. In step 3720, method3700 configures each tag based upon the assigned tag set. In one exampleof step 3720, optimizer 160 generates configuration data 170 with (a) aping rate of one-hundred pings per second for each tag 101 having itstag ID 208 within tag set 3512(1) and (b) a ping rate of one ping persecond for each tag having its tag ID 208 within either tag set 3512(2)or tag set 3512(3). In another embodiment, a ping rate for each tag setis determined based upon the number of tag IDs in each tag set and theSBWT. In yet another embodiment, configuring of each tag occursindependently within one of steps 3510, 3514, and 3516 within the loopof steps 3506-3518.

FIG. 38 shows an exemplary visual representation 3800 of tags 101grouped according to determined location within operational area 102 andperimeter of field of play 103, where tags within the perimeter of fieldof play 103 are shown within tag set 3512(1), tags 101 of team A thatare located on first sideline 3802 are shown within tag set 3512(2), andtags 101 of team B that are located on second sideline 3804 are shownwithin tag set 3512(3).

Using assumptions defined within Table 1 Example Parameters, ping rateallocator 3502 determines a different ping rate for tags 101 identifiedwithin each tag set 3512 based upon the ping budget of system 100, thenumber of priority tag sets 3512, and the number of tags 101 identifiedwithin each priority tag set 3512. In the example of Table 3 High/LowPrioritization Example, ping rate allocator 3502 sets the ping rate oftags 101 identified within tag set 3512(1) to 100 Hz, and the ping rateof tags 101 identified within tag sets 3512(2) and 3512(3) to 1 Hz. Witha ping rate increased from twenty-five to one-hundred pings per secondfor tags 101 identified within tag set 3512(1), the potential distancetraveled between valid Locates for those tags is reduced from 26.2inches (determined by the “Uniform Distribution Example” above) to 6.5inches.

TABLE 3 High/Low Prioritization Example Parameters Value Type LowPriority Players (tag set 3512(2)) 74 On the side lines Ping rate forLow priority 1 Pings per second Pings used from total ping budget 74Remaining ping budget 2326 High Priority Players (tag set 3512(1)) 22 Onthe field of play Ping setting/high priority player 100 Pings/Player/SecPings used from total ping budget 2200 Valid pings/player on field/sec55 Valid Locates/Sec Time between locates 0.0182 Seconds Potentialdistance traveled (yds) 0.18 Yards Potential distance traveled (inches)6.5 Inches Remaining ping budget 126

Continuing with the American football example, of the twenty-two playerson field of play 103, expected activity of each these players is basedupon their designated playing position. Ping Rate Allocator 3502 therebyfurther divides the twenty-two tags identified within tag set 3512(1)into three sub-tag sets 3512(1)(1), 3512(1)(2), and 3512(1)(3).

FIG. 39 shows exemplary sub-grouping of identifiers of tags 101 withintag set 3512(1) (shown as positioned on field of play 103) into sub-tagsets 3512(1)(1), 3512(1)(2), and 3512(1)(3). Although three sub-tag setsare used in this example, ping rate allocator 3502 may use more of fewersub-tag sets without departing from the scope hereof. Each sub-tag setis assigned a priority level based upon the expected activity level ofthe associated player and/or a priority of that player.

Table 4 High/Low & Position Prioritization Example shows exemplarysub-grouping of players based upon position and player priority.

TABLE 4 High/Low & Position Prioritization Example Parameters Value TypeSideline Players (Tag Sets 2 & 3) 74 On the side lines Ping rate for Lowpriority 1 Pings per second Pings used from total ping budget 74Remaining ping budget 2326 Linemen on Field (Tag Set 1.3) 10 5 Linemenper team on field Ping rate for linemen 30 30 pings/lineman Pings usedfrom budget for linemen 300 Valid pings/player on field/sec 16.5 ValidLocates/Sec Time between locates 0.0606 Seconds Potential distancetraveled (yds) 0.61 Yards Potential distance traveled (inches) 21.8Inches Remaining Ping budget 2026 total-sideline-linemen Mobile Playerson field (Tag Set 1.2) 8 Mobile players on field Ping setting/mobileplayer on field 100 Pings/Player/Sec Pings used from budget for linemen800 Valid pings/player on field/sec 55 Valid Locates/Sec Time betweenlocates 0.0182 Seconds Potential distance traveled (yds) 0.18 YardsPotential distance traveled (inches) 6.5 Inches Remaining Ping budget1226 total-sideline- linemen-mobile Skill Players on field (Tag Set 1.1)4 Skill players on field Ping setting/mobile player on field 300Pings/Player/Sec Pings used from budget for linemen 1200 Validpings/player on field/sec 165 Valid Locates/Sec Time between locates0.0061 Seconds Potential distance traveled (yds) 0.06 Yards Potentialdistance traveled (inches) 2.2 Inches Remaining Ping budget 26

Continuing with the example of American football, linemen do nottypically move very quickly, or travel a great distance, during anyparticular play of the game. Therefore, identifiers of tags 101 assignedto linemen (defined within the tag database during tagallocation/assignment for example) are grouped within a lowest prioritysub-tag set 3512(1)(3). In this example there are ten linemen on fieldof play 103 (five on each team). Ping rate allocator 3502 therebyconfigures tags 101 identified within sub-tag set 3512(1)(3) with a pingrate of 30 pings/sec, which results in a potential distance traveledbetween valid locates of 21.8 inches.

Mobile Players, which includes linebackers and running backs forexample, move more quickly than linemen and travel greater distancesthan the linemen in a play. In this example, tag IDs 208 of tags 101assigned to eight mobile players on field of play 103 (four on eachteam) are grouped within a middle priority sub-tag set 3512(1)(2). Pingrate allocator 3502 configures tags 101 identified within sub-tag set3512(1)(2) with a ping rate of 100 pings/sec, resulting in a potentialdistance traveled between valid Locates of 6.5 inches.

Skill Players, which may include receivers and defensive backs, are mostlikely the fastest moving players that cover the greatest distances in aplay. In this example there are four skill players (two on each team).Tag IDs 208 of tags 101 assigned to these skill players are thereforegrouped within the highest priority sub-tag set 3512(1)(1). Ping rateallocator 3502 configures tags 101 identified within sub-tag set3512(1)(1) with a highest ping rate of 300 pings/sec resulting in apotential distance traveled between valid locates of 2.2 inches.

FIG. 40 is a flowchart illustrating one exemplary method 4000 forsub-grouping of tag IDs 208 within a high priority tag set (e.g., tagset 3512(1)) into first, second, and third sub-tag sets (e.g., sub-tagsets 3512(1)(1), 3512(1)(2), and 3512(1)(3)). Method 4000 is for exampleimplemented within ping rate allocator 3502 of FIG. 35. Although threesub-tag sets are used in these examples, method 4000 may be modified touse more of fewer sub-tag sets without departing from the scope hereof.

In step 4002, method 4000 selects a first tag ID from the tag set. Inone example of step 4002, ping rate allocator 3502 selects a first tagID 208 from tag set 3512(1). In step 4004, method 4000 determines theplaying position of the player associated with the tag ID. In oneexample of step 4004, ping rate allocator 3502 accesses looks upassociated information of current tag ID 208 within a database definingtag assignments for example, to determine the position of a playerassociated with the tag ID.

Step 4006 is a decision. If, in step 4006, method 4000 determines thatthe player associated with the current tag ID is a lineman, method 4000continues with step 4008; otherwise method 4000 continues with step4010. In step 4008, method 4000 adds the current tag ID to the thirdsub-tag set. In one example of step 4008, current tag ID 208 is added tosub-tag set 3512(1)(3). Method 4000 then continues with step 4018.

Step 4010 is a decision. If, in step 4010, method 4000 determines thatthe player associated with the current tag ID is a mobile player, method4000 continues with step 4012; otherwise method 4000 continues with step4014. In step 4012, method 4000 adds the current tag ID to the secondsub-tag set. In one example of step 4012, current tag ID 208 is added tosub-tag set 3512(1)(2). Method 4000 then continues with step 4018.

Step 4014 is a decision. If, in step 4014, method 4000 determines thatthe player associated with the current tag ID is a skill player, method4000 continues with step 4016; otherwise method 4000 continues with step4018. In step 4016, method 4000 adds the current tag ID to the firstsub-tag set. In one example of step 4016, current tag ID 208 is added tosub-tag set 3512(1)(1). Method 4000 then continues with step 4018.

Step 4018 is a decision. If, in step 4018, method 4000 determines thatthere are more tag IDs to process, method 4000 continues with step 4020;otherwise method 4000 terminates. In step 4020, method 4000 selects thenext tag ID within the tag set. In one example of step 4020, ping rateallocator 3502 selects a next tag ID 208 from tag set 3512(1). Method4000 then continues with step 4004.

Steps 4002 through 4020 repeat to process all tag IDs within the tagset, and to add each tag ID to one of the first, second and thirdsub-tag sets.

Play Type

In addition to player positions, ping rate allocator 3502 may alsoconsider what type of play is about to be executed on the field whenconfiguring the ping rates of tags 101. Most sports, including Americanfootball, have a defined number of formations or situations. In Americanfootball, a team may line up in one of: a “short yardage” formation, a“kick off” formation, a “running” formation, and a “passing” formation,and so on. These formations are well known in the sport, together withexpected player motion resulting from each specific formation. Ping rateallocator 3502 compares relative locations of tags 101 on field of play103 against the relative positions of players within play formations3516 to determine a type of play that is likely to occur next. Playformations 3516 is for example a database of predetermined formationsthat result in a predictive play. By matching the location of tags 101of one or both teams on the field of play to formations within playformations 3516, ping rate allocator 3502 determines likely motion ofeach player and configures the tag 101 of these players accordingly.

FIG. 41 shows one exemplary short yardage formation 4100 in an Americanfootball game. Short yardage formation 4100 is typically used when theoffensive team needs a very small amount of yardage on the upcomingplay. The teams typically line up in a tight formation, where allplayers are bounded by a bounding rectangle 4102 of a first size. Shortyardage formation 4100 almost invariably results in low speed motion andvery limited distances traveled by all players on field of play 103.Therefore, ping rate allocator 3502, upon matching short yardageformation 4100 within play formations 3516, uses high low ping ratealgorithm shown in method 3700 of FIG. 37 (and detailed within Table 3High/Low Prioritization Example and FIG. 38) to assign ping rates toeach tag 101.

FIG. 42 shows one exemplary passing formation 4200 in an Americanfootball game. Passing formation 4200 is very commonly used during agame when a team is hoping to make a passing play to advance the ballfurther up the field as compared to a short yardage play. As shown,players in passing formation 4200 are more spread out, having a boundingrectangle 4202 of a second size that is significantly larger than thefirst size of bounding rectangle 4102 of short yardage formation 4100.In particular, within passing formation 4200, skill players arepositioned wide from the linemen. Passing formation 4200 has a muchhigher likelihood of differentiation in the speed, and distancestraveled, by athletes based on their position, as compared to athletemovement with short yardage formation 4100. Therefore, ping rateallocator 3502 uses the more complex High/Low and Positionprioritization as shown in FIG. 39, and detailed in Table 4 High/Low &Position Prioritization Example.

In the examples of FIGS. 41 and 42, the bounding rectangle is used todetermine the type of play likely to occur. In an alternate embodiment,the relationship between the determined positions of the players is usedto determine the expected type of play. In another embodiment, one ormore ping rates of tags 101 associated with certain players (e.g., thequarterback in American Football) are given fixed ping rates such thataccuracy of location of these players is maintained.

Receiver Event Allocation

Once receivers 104 are physically mounted, angled and aimed, the primaryreceiver property to adjust, within programmable gain stage 604, FIG. 6,is gain. Programmable gain stage 604 determines receiver sensitivity andhow well it detects pings 402. When set to a maximum gain (highestsensitivity), the receiver detects the highest number of pings 402 andthus the average number of receiver events per ping increases.Similarly, when set to a minimum gain (lowest sensitivity), the receiverdetects the lowest number of pings 402 and thus the average number ofreceiver events per ping decreases. System bandwidth of object trackingsystem 100, FIG. 1, is defined as the total number of receiver events110 that system 100 processes without becoming saturated and overloaded.

FIG. 43 shows optimizer 160 of FIG. 1 illustrating exemplary detail forcontrolling gain of receiver 104. In particular, optimizer 160 isconfigured with a receiver event allocator 4302 that controlsprogrammable gain stage 604 of each receiver 104. Receiver eventallocator 4302 operates to automatically adjust gain properties of eachreceiver 104 within system 100 such that system 100 operates at, ornear, eighty-five percent of system bandwidth for example. Otherpercentages of the system bandwidth may be used without departing fromthe scope hereof. This allows system 100 to process as many pings 402 aspossible, maximizing accuracy of locate data 120, without riskingoverload of system 100 by exceeding the system bandwidth. That is,without the bandwidth control provided by receiver event allocator 4302,system 100 would be at risk of exceeding the system bandwidth andthereby causing delay and errors within locate data 120.

As described above, each receiver 104 generates one receiver event 110for each ping 402 detected. Depending on the physical mounting(location, angle & aim) of receivers 104, the location of tags 101relative to the receivers 104, and the gain (i.e. sensitivity) of eachreceiver 104, each ping 402 generated by tags 101 may be detected by anynumber (zero to all) of receivers 104, thereby resulting in no receiverevents 110 or resulting in any number of receiver events 110 up to amaximum of one receiver event 110 from each receiver 104 within system100. For example, where system 100 includes twelve receivers 104, eachping 402 may result in zero to twelve receiver events 110. As notedabove, system 100 operates most efficiently, in terms of accuracy oflocate data 120 and system bandwidth use, when the average number ofreceiver events 110 per ping 402 is greater than four and less thanfive.

FIG. 44 shows system 100 configured with twelve receivers 104(1)-(12).Assumptions for a unified gain example are shown in Table 5 Unified GainAssumptions.

TABLE 5 Unified Gain Assumptions System Bandwidth 12,750 ReceiverEvents/Second System Bandwidth Target (SBWT): 10,880 ReceiverEvents/Second 85% of System Bandwidth Receivers in system 12 Tags inSystem 96 All tags are of equal priority Tag Ping Rate 25 Pings/Second

Where each ping 402 generated by each tag 101 is detected by eachreceiver 104 within system 100, twenty-eight-thousand-eight-hundredreceiver events 110 are generated each second, as shown in Equation 1.

96*25*12=28,800   Equation 1

Since this is more than double the system bandwidth of 12,750 receiverevents/second, system 100 would be overloaded and potentially enter afailure condition. Therefore, receiver event allocator 4302 isconfigured to control gain properties of receivers 104 such that, onaverage, each ping 402 is detected by four-and-a-half receivers 104. Thenumber of receiver events 110 generated is thereby reduced toten-thousand-eight-hundred, as shown in Equation 2.

96*25*4.5=10,800   Equation 2

In this generalized example, reducing the number of receiver events 110to ten-thousand-eight-hundred provides a high percentage of successfullocates within locate data 120 and operates system 100 at SBWT. Receiverevent allocator 4302 processes locate data 120, determines an averagenumber of receiver events 110 generated for each ping 402, andautomatically adjusts programmable gain stage 604 of each receiver 104such that this average is equal to four-and-a-half.

There are many conditions which, alone or in combination, may affect thesignal strength of ping 402 before it reaches receiver 104. For example,(a) obstructions (such as human bodies) in the “line of sight” betweentag 101 and receiver 104, (b) rain and other weather conditions, and (c)distance between tag 101 and receiver 104. Each condition reduces thesignal strength of ping 402 received by receiver 104. When the signalstrength of ping 402 falls below a certain level due to these changingconditions, then receiver 104 does not detect ping 402 at certain gainsettings. Receiver event allocator 4302 operates to dynamically adjustthe gains of receivers 104 in response to these changing conditions andthus adjusts the sensitivity of receivers 104 to detecting ping 402.

FIG. 45 is a flowchart illustrating one exemplary method 4500 forautomatic optimization of object tracking system 100 of FIG. 44 byautomatically adjusting gain of all receivers 104 based upon averagereceiver events per second within system 100. Method 4500 is for exampleimplemented within receiver event allocator 4302 of FIGS. 43 and 44.

In step 4502, method 4500 sets the gain of all receivers to an 85%level. In one example of step 4502, receiver event allocator 4302 sendsconfiguration data 170 to processing hub 150 which then sends gain data4320 to each receiver 104. Each receiver 104 then sets (e.g., fromcommunication interface 608) the gain of programmable gain stage 604based upon gain data 4320.

In step 4504, method 4500 calculates the average receiver events persecond within system 100. In one example of step 4504, receiver eventallocator 4302 processes locate data 120 and determines average receiverevents per second 4310.

Step 4506 is a decision. If, in step 4506, method 4500 determines thatthe average receiver events per second is greater than the SBWT plusfive percent, method 4500 continues with step 4508; otherwise method4500 continues with step 4510. In step 4508, method 4500 decreases thegain of receivers. In one example of step 4508, receiver event allocator4302 sends configuration data 170 containing a reduced gain value toprocessing hub 150, which then sends the reduces gain value as gain data4320 to each receiver 104. Within each receiver 104, communicationinterface 608 sets programmable gain stage 604 based upon gain data4320.

Step 4510 is a decision. If, in step 4510, method 4500 determines thatthe average receiver events per second is less than SBWT minus fivepercent, method 4500 continues with step 4512; otherwise method 4500continues with step 4504. In step 4512, method 4500 increases the gainof receivers. In one example of step 4512, receiver event allocator 4302sends configuration data 170 containing an increased gain value toprocessing hub 150, which then sends the increased gain value as gaindata 4320 to each receiver 104. Within each receiver 104, communicationinterface 608 sets programmable gain stage 604 based upon gain data4320.

Steps 4504 through 4512 repeat periodically (e.g., once per second) toautomatically adjust gain of all receivers 104 based upon the averagenumber of receiver events 110 within system 100. Receiver eventallocator 4302 implements method 4500 to periodically and/or continuallymonitor and adjust average receiver events per second 4310 to be withinfive percent of SBWT thereby preventing receiver event overload ofsystem 100, while also maintaining sufficient receiver events tocalculate locates for locate data 120.

The example of FIGS. 43, 44 and 45 illustrates the general concepts ofcontrolling gain of receivers 104 within system 100 based upon changingconditions. A further advancement of receiver gain control to maximizethe Locate accuracy for high priority tags is achieved within system 100by grouping identities of receivers 104 into receiver priority groups4330. Gains of receivers 104 identified within each priority receivergroup 4330 are controlled independently of receivers identified withinother priority groups by determining a locate-to-ping ratio for thesehigh priority tags, while remaining within system bandwidth limitations.

Achieving this balance requires dynamic monitoring of activity ofreceiver events 110, on a per tag 101 basis, and adjusting the gain ofeach receiver 104 individually to allocate the system bandwidth (i.e.,the number of receiver events received by processing hub 150) toreceivers 104 thereby providing system 100 with the best configurationto maximize the locate-to-ping ratio, and thus the accuracy of theassociated locates, of the high priority tags in the system, whileremaining safely under the system bandwidth limitation.

FIG. 46 shows tag data 4311 of FIG. 43 in further exemplary detail.Receiver event allocator 4302 constantly monitors receiver events 110and, individually for each tag 101, whether each ping results in a validlocate or not, determines, for a specified sample period (e.g., twoseconds): a number of pings 4612, a locate-to-ping ratio 4614, anaverage receiver events 4616, and, for each receiver, a percentage ofpings detected 4618. Number of pings 4612 is the number of pings 402transmitted by tag 101 for the specified sample period (e.g., fifty,where the tag ping rate is twenty-five per second and the specifiedsample period is two seconds). Locate-to-ping ratio 4614 is a ratio ofthe number of locates resulting from detected pings 402 of tag 101 overthe specified sample period to the number of pings 4612 for that tag.Average receiver events 4616 is the average number of receiver events110 for tag 101 over the specified sample period. Together with numberof pings 4612, average receiver events 4616 may be used to calculate theaverage system bandwidth consumed by each individual tag 101. For eachreceiver 104, percentage of pings detected 4618 is the number of pings402 detected for tag 101 during the specified sample period,irrespective of whether the ping results in a locate. Percentage ofpings detected 4618 may be used to track which receivers are being usedat any given time.

Tag data 4311 is aggregated based upon tag sets 3512, and optionallysub-tag sets thereof, as shown in FIGS. 35, 38, and 39. Continuing withthe American football example of FIGS. 36-42 and 44, three exemplary tagsets 3512(1)-(3) are used to aggregate tag data 4311. In terms ofallocating receiver events, tag set 3512(1) “Players On Field” is givenpriority by receiver event allocator 4302 over tag sets 3512(2) and3512(3) that identify tags of plays off the field of play.

Tag Set Boundary

FIG. 47 shows exemplary tag set boundaries 4702 that bound tags 101based upon tag sets 3512 of FIGS. 35, 38 and 39. Receiver eventallocator 4302 determines each tag set boundary 4702 as havingcoordinates of the minimum rectangle, aligned along axis 4704 of system100, that contains all tags 101 within the associated tag set 3512. Inparticular, the location of tags 101 identified within tag set 3512(1)are bounded by tag set boundary 4702(1), the locations of tags 101identified within tag set 3512(2) are bounded by tag set boundary4702(2), and the locations of tags 101 identified within tag set 3512(3)are bounded by tag set boundary 4702(3).

Receiver Priority

Receiver event allocator 4302 determines receiver groups 4330 based uponthe importance of each receiver 104 for determining Locates of tags 101identified within high priority tag set 3512(1). In the example of FIG.47, there are three receiver groups 4330(1)-(3). Receiver groups 4330are determined by receiver event allocator 4302 using receiver grouprules 4332 that include, for example: receiver group 4330(1) identifiesthe four receivers 104 that define the smallest rectangle 4706encompassing tag set boundary 4702(1) (i.e., enclosing all high prioritytags 101 identified within tag set 3512(1)); receiver group 4330(2) isdefined as identifying receivers 104 located along the sides ofrectangle 4706 defined by receiver group 4330(1), whether thesereceivers are on the line or at a distance perpendicular to the line;and receiver group 4330(3) is defined as identifying all receiversoutside rectangle 4706 defined by receiver group 4330(1).

It is important to note that tag set boundaries 4702 and receiver groups4330 change as tags 101 identified within tag set 3512(1) (i.e., theplayers associated with the identified tags) move around on field ofplay 103. Therefore, tag set boundaries 4702 and receiver groups 4330are continually evaluated.

Dynamic Receiver Gain Adjustment:

Receiver event allocator 4302 continuously adjusts gain of each receiver104 to maximize locate-to-ping ratio 4314 of tags 101 identified withinthe highest priority tag set 3512(1) while preserving system bandwidthby carefully allocating receiver events 110 that are not directlyassociated with tags 101 grouped within tag set 3512(1). The gain of allreceivers 104 is initially set to a nominal gain value (e.g.,eighty-five percent of maximum gain). Receiver event allocator 4302thereafter adjusts the gain of each receiver 104 based on receivergroups 4330 to maximize locate-to-ping ratio 4314 of tags 101 identifiedwithin high priority tag set 3512(1), at the expense of tags 101identified within lower priority tag sets 3512(2) and 3512(3), whilekeeping the total number of receiver events 110 handled by system 100 atthe SBWT.

The first, and arguably most important, step of dynamic receiver gainadjustment by receiver event allocator 4302 targets maximizing theperformance of tags 101 identified within high priority tag set 3512(1).Receiver event allocator 4302 allocates a large percentage (e.g.,seventy percent) of SBWT, known as the Tag Set 1 Bandwidth Target“TS1BT”, to this first stage of receiver adjustment. Continuing with theabove American football example, TS1BT is set to 7,586 receiver eventsper second as shown in Equation 3.

12,750*0.85*0.70=7,586   Equation 3

FIG. 48 is a flowchart illustrating one exemplary method 4800 forautomatic optimization of object tracking system 100 of FIG. 1 bycontrolling gain of receivers 104 based upon receiver events 110associated with highest priority tag set 3512(1) of FIG. 35. Method 4800is for example implemented within receiver event allocator 4302 and isinvoked continuously or periodically to manage system bandwidth usage ofsystem 100. FIGS. 49 and 50 are flowcharts showing one exemplarysub-method 4900 for decreasing usage of the system bandwidth of system100. Sub-method 4900 is invoked from method 4800 for example. FIGS. 51and 52 are flowcharts showing one exemplary sub-method 5100 forincreasing usage of system bandwidth of system 100. Sub-method 5100 isinvoked from method 4800 for example. FIGS. 48 through 52 are bestviewed together with the following description.

Using method 4800 and sub-methods 4900 and 5100, receiver eventallocator 4302 controls system bandwidth usage of system 100. Gainsettings of receivers 104 are automatically decreased when thedetermined total number of receiver events for tags 101 identifiedwithin high priority tag set 3512(1) exceeds TS1BT by more than fivepercent. Similarly, receiver event allocator 4302 automaticallyincreases gain settings of receivers 104 when the determined totalnumber of receiver events for tags 101 identified within high prioritytag set 3512(1) falls below TS1BT by more than five percent.

To preserve the locate-to-ping ratio of tags 101 identified within highpriority tag set 3512(1), when reducing gain settings (i.e., to reducethe number of receiver events 110 occurring within system 100), receiverevent allocator 4302 first reduces gain settings of receivers identifiedwithin the lowest priority receiver group (e.g., receiver group4330(3)). When further reduction in the receiver events received isrequired, and the gain setting of receivers identified within the lowestpriority receiver group have been reduced to a minimum setting, receiverevent allocator 4302 then reduces the gain setting of receiversidentified within the middle priority receiver group (e.g., receivergroup 4330(2)). Finally, when further reduction of the number ofreceiver events is required and the gain setting of receivers identifiedwithin the middle priority receiver group is set to a minimum gainsetting, receiver event allocator 4302 then reduces the gain setting ofreceivers identified within the high priority receiver group (e.g.,receiver group 4330(1)).

When increasing the gain setting of receivers 104 due to insufficientreceiver events 110 being received for tags 101 identified withinhighest priority tag set 3512(1), receiver event allocator 4302 firstincreases the gain setting of receivers identified within the highestpriority receiver group (e.g., receiver group 4330(1)), since thesereceivers are most likely to detect pings from tags 101 identifiedwithin the highest priority tag set 3512(1). If further increase in thenumber of receiver events is desired and the gain setting of receiversidentified within the highest priority receiver group is at a maximumgain setting, receiver event allocator 4302 then increases the gains ofreceivers identified within the middle priority receiver group (e.g.,receiver group 4330(2)). If still further increase in the number ofreceiver events is desired and the gain setting of receivers identifiedwithin the middle priority receiver group is also at a maximum gainsetting, receiver event allocator 4302 then increases the gain settingof receivers identified within the lowest priority receiver group (e.g.,receiver group 4330(3)).

Thus, receivers 104 identified within the highest priority receivergroup 4330(1) are the first to have gain setting increased whenadditional receiver events are desired, and are the last to have gainsetting decreased when the number of receiver events is too high.

In step 4802, method 4800 determines receiver groups. In one example ofstep 4802, receiver event allocator 4302 determines receiver groups4330(1), 4330(2), and 4330(3) based upon receiver group rules 4332 andlocate data 120.

In step 4804, method 4800 sets receiver gains to eighty-five percent ofthe maximum gain value. In one example of step 4804, receiver eventallocator 4302 sends configuration data 170 defining, for each receiver104, a gain value of eighty-five percent of the maximum gain value toprocessing hub 150, which in turn sends gain data 4320 including thegain value, to each receiver 104.

In step 4806, method 4800 determines receiver events per second for thehigh priority tag set. In one example of step 4806, receiver eventallocator 4302 processes locate data 120 to determine a total count ofreceiver events 110 associated with pings 402 of tags 101 identifiedwithin tag set 3512(1) over a selected sample period, and thencalculates the number of receiver events per second.

Step 4808 is a decision. If, in step 4808, method 4800 determines thatthe receiver events per second determined in step 4806 is greater thanTS1BT+five percent, method 4800 continues with step 4810; otherwisemethod 4800 continues with step 4812.

In step 4810, method 4800 invokes sub-method 4900 to reduce bandwidthusage of system 100. Method 4800 then continues with step 4806.

Step 4812 is a decision. If, in step 4812, method 4800 determines thatthe receiver events per second determined in step 4806 is less thanTS1BT—five percent, method 4800 continues with step 4814; otherwisemethod 4800 continues with step 4806.

In step 4814, method 4800 invokes sub-method 5100 to increase bandwidthusage of system 100. Method 4800 then continues with step 4806.

Steps 4806 through 4814 repeat continuously such that usage of systembandwidth of system 100 is controlled based upon receiver events 110associated with tags 101 identified within highest priority tag set3512(1).

In step 4902, sub-method 4900 determines receiver events per second fortags identified within the high priority tag set. In one example of step4902, receiver event allocator 4302 processes locate data 120 todetermine a total count of receiver events 110 associated with pings 402of tags 101 identified within tag set 3512(1) over a selected sampleperiod, and then calculates the number of receiver events per second.

Step 4904 is a decision. If, in step 4904, sub-method 4900 determinesthat the receiver events per second of step 4902 is greater than TS1BT,sub-method 4900 continues with step 4906; otherwise sub-method 4900returns control to method 4800.

Step 4906 is a decision. If, in step 4906, sub-method 4900 determinesthat gain settings of receivers identified within receiver group 4330(3)are set to a minimum gain setting, sub-method 4900 continues with step4910; otherwise sub-method 4900 continues with step 4908. In step 4908,sub-method 4900 decreases gain settings of receivers identified withinreceiver group 4330(3). In one example of step 4908, receiver eventallocator 4302 sends configuration data 170 containing reduced gainvalues for receivers 104 identified within receiver group 4330(3) toprocessing hub 150; processing hub 150 then sends gain data 4320containing the reduced gain value to receivers 104(4), 104(5), 104(7),and 104(8) identified within receiver group 4330(3). Sub-method 4900then continues with step 4902. Steps 4902 through 4906 repeat until (a)receiver events per second of step 4902 is not greater than TS1BT,whereupon sub-method 4900 returns control to method 4800, or (b) thegain setting of receivers 104 identified within receiver group 4330(3)is at a minimum gain setting, whereupon sub-method 4900 continues withstep 4910.

Step 4910 is similar to step 4902. In step 4910, sub-method 4900determines receiver events per second for tags identified within thehigh priority tag set.

Step 4912 is a decision. If, in step 4912, sub-method 4900 determinesthat the receiver events per second of step 4910 is greater than TS1BT,sub-method 4900 continues with step 4914 otherwise sub-method 4900returns control to method 4800.

Step 4914 is a decision. If, in step 4914, sub-method 4900 determinesthat gain settings of receivers identified within receiver group 4330(2)are set to a minimum gain setting, sub-method 4900 continues with step4918; otherwise sub-method 4900 continues with step 4916. In step 4916,sub-method 4900 decreases gain settings of receivers identified withinreceiver group 4330(2). In one example of step 4916, receiver eventallocator 4302 sends configuration data 170 containing reduced gainvalues for receivers 104 identified within receiver group 4330(2) toprocessing hub 150, which then sends gain data 4320 containing thereduced gain value to receivers 104(2), 104(6), 104(10), and 104(12)identified within receiver group 4330(2). Sub-method 4900 then continueswith step 4910. Steps 4910 through 4916 repeat until (a) receiver eventsper second of step 4910 is not greater than TS1BT, whereupon sub-method4900 returns control to method 4800, or (b) the gain setting ofreceivers 104 identified within receiver group 4330(2) is at a minimumgain setting, whereupon sub-method 4900 continues with step 4918.

Step 4918 is similar to steps 4902 and 4910. In step 4918, sub-method4900 determines receiver events per second for tags identified withinthe high priority tag set.

Step 4920 is a decision. If, in step 4920, sub-method 4900 determinesthat the receiver events per second of step 4918 is greater than TS1BT,sub-method 4900 continues with step 4922 otherwise sub-method 4900returns control to method 4800.

Step 4922 is a decision. If, in step 4922, sub-method 4900 determinesthat gain settings of receivers identified within receiver group 4330(1)are set to a minimum gain setting, sub-method 4900 returns control tomethod 4800; otherwise sub-method 4900 continues with step 4924. In step4924, sub-method 4900 decreases gain settings of receivers identifiedwithin receiver group 4330(1). In one example of step 4924, receiverevent allocator 4302 sends configuration data 170 containing reducedgain values for receivers 104 identified within receiver group 4330(1)to processing hub 150, which then sends gain data 4320 containing thereduced gain value to receivers 104(1), 104(3), 104(9), and 104(11)identified within receiver group 4330(1). Sub-method 4900 then continueswith step 4918. Steps 4918 through 4924 repeat until (a) receiver eventsper second of step 4918 is not greater than TS1BT, whereupon sub-method4900 returns control to method 4800, or (b) the gain setting ofreceivers 104 identified within receiver group 4330(1) is at a minimumgain setting, whereupon sub-method 4900 returns control to method 4800.

In step 5102, sub-method 5100 determines receiver events per second fortags of the high priority tag set. In one example of step 5102, receiverevent allocator 4302 processes locate data 120 to determine a totalcount of receiver events 110 associated with pings 402 of tags 101identified within tag set 3512(1) over a selected sample period, andthen calculates the number of receiver events per second.

Step 5104 is a decision. If, in step 5104, sub-method 5100 determinesthat the receiver events per second of step 5102 is less than TS1BT,sub-method 5100 continues with step 5106; otherwise sub-method 5100returns control to method 4800.

Step 5106 is a decision. If, in step 5106, sub-method 5100 determinesthat gain settings of receivers identified within receiver group 4330(1)are set to a maximum gain setting, sub-method 5100 continues with step5110; otherwise sub-method 5100 continues with step 5108. In step 5108,sub-method 5100 increases gain settings of receivers identified withinreceiver group 4330(1). In one example of step 5108, receiver eventallocator 4302 sends configuration data 170 containing increased gainvalues for receivers 104 identified within receiver group 4330(1) toprocessing hub 150, which then sends gain data 4320 containing theincreased gain value to receivers 104(1), 104(3), 104(9), and 104(11)identified within receiver group 4330(1). Sub-method 5100 then continueswith step 5102. Steps 5102 through 5106 repeat until (a) receiver eventsper second of step 5102 is not less than TS1BT, whereupon sub-method5100 returns control to method 4800, or (b) the gain setting ofreceivers 104 identified within receiver group 4330(1) is at a maximumgain setting, whereupon sub-method 5100 continues with step 5110.

Step 5110 is similar to step 5102. In step 5110, sub-method 5100determines receiver events per second for tags identified within thehigh priority tag set.

Step 5112 is a decision. If, in step 5112, sub-method 5100 determinesthat the receiver events per second of step 5110 is less than TS1BT,sub-method 5100 continues with step 5114 otherwise sub-method 5100returns control to method 4800.

Step 5114 is a decision. If, in step 5114, sub-method 5100 determinesthat gain settings of receivers identified within receiver group 4330(2)are set to a maximum gain setting, sub-method 5100 continues with step5118; otherwise sub-method 5100 continues with step 5116. In step 5116,sub-method 5100 increases gain settings of receivers within receivergroup 4330(2). In one example of step 5116, receiver event allocator4302 sends configuration data 170 containing increased gain values forreceivers 104 identified within receiver group 4330(2) to processing hub150, which then sends gain data 4320 containing the increased gain valueto receivers 104(2), 104(6), 104(10), and 104(12) identified withinreceiver group 4330(2). Sub-method 5100 then continues with step 5110.Steps 5110 through 5116 repeat until (a) receiver events per second ofstep 5110 is not less than TS1BT, whereupon sub-method 5100 returnscontrol to method 4800, or (b) the gain setting of receivers 104identified within receiver group 4330(2) is at a maximum gain setting,whereupon sub-method 5100 continues with step 5118.

Step 5118 is similar to steps 5102 and 5110. In step 5118, sub-method5100 determines receiver events per second for tags identified withinthe high priority tag set.

Step 5120 is a decision. If, in step 5120, sub-method 5100 determinesthat the receiver events per second of step 5118 is less than TS1BT,sub-method 5100 continues with step 5122 otherwise sub-method 5100returns control to method 4800.

Step 5122 is a decision. If, in step 5122, sub-method 5100 determinesthat gain settings of receivers identified within receiver group 4330(3)are set to a maximum gain setting, sub-method 5100 returns control tomethod 4800; otherwise sub-method 5100 continues with step 5124. In step5124, sub-method 5100 increases gain settings of receivers identifiedwithin receiver group 4330(3). In one example of step 5124, receiverevent allocator 4302 sends configuration data 170 containing increasedgain values for receivers 104 identified within receiver group 4330(3)to processing hub 150, which then sends gain data 4320 containing theincreased gain value to receivers 104(4), 104(5), 104(7), and 104(8)identified within receiver group 4330(3). Sub-method 5100 then continueswith step 5118. Steps 5118 through 5124 repeat until (a) receiver eventsper second of step 5118 is not less than TS1BT, whereupon sub-method5100 returns control to method 4800, or (b) the gain setting ofreceivers 104 identified within receiver group 4330(3) is at a maximumgain setting, whereupon sub-method 5100 returns control to method 4800.

As shown in the above examples, a hysteresis value of +/−five percent isused, however, other values may be used without departing from the scopehereof. For example, a ten percent hysteresis may results in fewer gaincontrol settings being generated by receiver event allocator 4302.

Receiver event allocator 4302 may perform a second stage of dynamicreceiver gain adjustment to improve performance of tags within lowerpriority tag sets (e.g., tag sets 3512(2) and 3512(3)) by using theremaining portion (e.g., thirty percent) of the SBWT. Continuing withthe American football example, this second stage manages three thousandtwo hundred and fifty one receiver events as shown by Equation 4.

(12750*0.85*0.30)=3,251   Equation 4

Receiver event allocator 4302 thereby allocates these receiver eventsusing a method similar to method 4800 and sub-methods 4900 and 5100, byfocusing on receiver events 110 received for tags 101 identified withinthe lower priority tag sets. However, for these lower priority tagssets, the gain setting of the receivers 104 are only increased (and notdecreased) to use all remaining available system bandwidth, onceperformance of tags 101 identified within the high priority tag set(e.g., tag set 3512(1)) is optimal. By not decreasing the gain settingsof receivers using this second stage of receiver gain adjustment,receiver event allocator 4302 avoids inadvertently decreasing the gainof receivers critical to tags identified within high priority tag set3512(1).

Receiver Modifications

FIG. 53 shows further exemplary detail of receiver 104 of FIG. 1.Receiver 104 includes transmit/receive antenna 602, programmable gainstage 604, analog signal detection electronics 606, and interface 608for communicating with processing hub 150 and including signalprocessing electronics 5308. Tag 101 transmits a very low power (1 mW)signal with a 6.55 GHz center frequency and +/−200 Mhz. The totalfrequency range of the transmission from tag 101 is 6.35-6.75 GHz.Receiver 104 is tuned to receive at 6.55 GHz center frequency. FIG. 54shows a graph 5400 illustrating one exemplary response curve of an“off-the-shelf” receiver with unity gain at approximately 6.6 GHz.

Absent other wireless signals within the operational environment (i.e.,operational area 102) of system 100, detecting of pings 402 using the“off-the-shelf” receivers is relatively simple. In the typicalenvironments where UWB tracking systems are deployed, such as hospitalsand manufacturing plants, there is a high level of wireless signalcoordination and interference from other wireless systems within thefrequency range of 6-7 GHz does not occur. However, system 100 operateswithin a “Game Day” environment at a major sporting venue where there isa wide spectrum of other wireless systems including, but not limited to,venue WiFi at 5.8 GHZ, coaching communication systems at variedfrequencies, wireless broadcast camera systems at 2.4, 4.6, 5.8, and 7.1GHz and transmission towers located outside the venue typicallytransmitting at 7.0 GHz or higher. Although, on paper, it seems thatthese other wireless systems do not transmit at the frequency range(6.35-6.75 GHz) used by system 100, and would therefore not interfere,in the real world, other wireless systems of the Game Day environmentmay cause the “off-the-shelf” receivers to be unable to detect the lowpower pings 402 from tags 101.

Many factors prevent the successful use of “off-the-shelf” receiverswithin the Game Day environment. For example, tags 101 are tuned totransmit at approximately 6.55 GHz, whereas, as shown in FIG. 54, theresponse curve of the “off-the-shelf” receiver has a center frequency(unity gain, or 0 dB attenuation) at 6.6 GHz. The attenuation of the“off-the-shelf” receiver at 6.35 GHz is ˜14 dB and at 6.75 GHZ is ˜9 dB.Also note that the response curve of FIG. 54 shows that whileattenuated, signals below 6.35 GHz and above 6.75 GHz are allowed topass through the front end of the “off-the-shelf” receiver. Since tags101 transmit in the 6.35-6.75 GHz range, ping 402 passes through thefront end of the “off-the-shelf” receiver; however, since signal fromtag 101 is transmitted at a power of 1 mW, these signals are not asstrong as signals from other systems within the Game Day environment.For example, a wireless broadcast camera typically transmits signals ata power of 250 mW. Although the center frequency of these other wirelesssystems are outside the 6.35-6.75 GHz range, the higher output power attheir center frequency typically results in harmonics and straytransmissions at frequencies close to the 6.35-6.75 GHz range.

Since the “off-the-shelf” receiver front end attenuates, rather thanrejects, signals outside the 6.35-6.75 GHz range, some portion of theenergy from these other wireless systems passes through the front end ofto reach the analog detection electronics 606. Given the significantlystronger signals from these other transmission sources (250 timesstronger from the wireless broad cast camera), the energy passingthrough the front end of the “off-the-shelf” receiver may saturate theanalog detection electronics 606 and prevent detection of ping 402 fromtag 101.

Band Pass Filtering

FIG. 55 is a composite graph 5500 showing the response curve of graph5400, FIG. 54, and a desired frequency range 5502 of 6.35-675 GHz.Frequencies outside desired frequency range 5502 (i.e., below 6.35 GHzand above 6.75 GHz) are not desired. As noted above, energy from asignal at a frequency close to the desired range may pass through thefront end to be received by the analog detection circuitry of the“off-the-shelf” receiver. Since ping 402 is transmitted at 1 mW, it doesnot take very much stray energy from a signal at a frequency outsidedesired frequency range 5502 to disrupt detection of the ping.

Receiver 104 is improved, as compared to the “off-the-shelf” receiversdescribed above, by inserting a band-pass filter 5320 immediately afterantenna 602 and before programmable gain stage 604, as shown in FIG. 53.An ideal band-pass filter has unity gain in the pass band (i.e.,6.35-6.75 GHz) and 100% attenuation outside the pass band (i.e.,frequencies below 6.35 GHz and above 6.75 GHz). Desired frequency range5502 represents an ideal 6.35-6.75 GHz band-pass filter implementation.In practice, at UWB frequencies, the introduction of any circuitelements in the signal path introduces some level of attenuation, knownas “insertion loss”. Insertion loss thereby degrades signals from tags101. Therefore, a critical design goal of band-pass filter 5320 is tominimize insertion loss. In practice, analog filters also do not have avertical roll off (i.e., fast change in response) between the pass andthe reject bands. However, the steeper the roll off between pass bandand reject bands, the more effective the band-pass filter is in blockingundesired energy from passing through to the programmable gain stage 604and detection electronics 606. Thus, a second critical design goal ofband-pass filter 5320 is to provide a very steep roll off between thepass band and the reject bands.

Physical Implementation:

FIG. 56 shows exemplary components that are used to upgrade an“off-the-shelf” receiver (i.e., a commercially available UWB receiver)to a band-pass filter enhanced UWB Receiver (i.e., receiver 104) for usewithin a game day environment. In particular, FIG. 56 shows one6.35-6.75 GHz band-pass filter stage 5320, one extended coax cable 5604,one extended data ribbon cable 5606, one coax coupler 5608, oneextrusion extension 5610, and four extra-long housing screws 5612.

FIG. 57 is a flowchart illustrating one exemplary method 5700 formodifying and improving an “off-the-shelf” receiver to create a receiver104 that receives ping 402 when operating within a game day environment.FIG. 58 shows an assembly view of receiver 104 and of an “off-the-shelf”receiver 5850. FIG. 59 is a side view showing receiver 104 assembled andin comparison to the assembled “off-the-shelf” receiver 5850. FIGS. 56through 59 are best viewed together with the following description.

In step 5702, method 5700 removes the four housing screws and detachesthe antenna. In one example of step 5702, four housing screws areremoved and antenna 602 is detached from housing 5802. In step 5704,method 5700 removes the existing coax and data ribbon cables. In step5706, method 5700 connects the extended coax cable to the coax connectorin the housing. In one example of step 5706, extended coax cable 5604 iscoupled to a coax connector within housing 5802 of receiver 104. In step5708, method 5700 connects the extended data ribbon cable to the ribbonheader in the receiver housing. In one example of step 5708, extendedribbon cable 5606 connects to a ribbon cable header within housing 5802.In step 5710, method 5700 slides the extrusion extension over theextended coax and data ribbon cables. In one example of step 5710,extrusion extension 5610 is slid over extended coax cable 5604 andextended ribbon cable 5606. In step 5712, method 5700 connects one endof the band-pass filter to the extended coax cable. In one example ofstep 5712, a first end of band pass filter 5320 couples to the free endof extended coax cable 5604. In step 5714, method 5700 connects the freeend of the band-pass filter to the coax coupler. In one example of step5714, the second end of band pass filter 5320 couples with a first endof coax coupler 5608. In step 5716, method 5700 connects the other endof the coax coupler to the coax connector on the antenna. In one exampleof step 5716, the second end of coax coupler 5608 is coupled with a coaxconnector of antenna 602. In step 5718, method 5700 connects theextended data ribbon cable to the ribbon header on the antenna. In oneexample of step 5718, the second end of extended ribbon cable 5606 iscoupled with a ribbon cable header on antenna 602.

In step 5720, method 5700 carefully slides the assembly together andsecure with 4 extra-long housing screws. In one example of step 5720,housing 5802, extruded extension 5610, and antenna 602 are slid togetherand secured with extra-long housing screws 5612.

In step 5722, method 5700 tests receiver 104 to make certain it was notcompromised during the upgrade and that significant insertion losseswere not incurred. In one example of step 5722, receiver 104 isevaluated within a test chamber to ensure that band pass filter 5320does not introduce excessive insertion loss or cause excessiveattenuation in the pass band.

Dynamic Antenna Orientation Adjustment

FIGS. 60 and 61 show one exemplary receiver 6000 having a receiver body6002 and an antenna 6004 with remotely controlled pan and tiltfunctionality. Antenna 6004 is articulated 6016 (e.g., by servo motors)in response to received commands from processing hub 150 for example.FIG. 60 is a top view of receiver 6000 illustrating pan movement 6006 ofantenna 6004 relative to receiver body 6002 and FIG. 61 is a side viewof receiver 6000 illustrating tilt movement 6008 of antenna 6004relative to receiver body 6002. Receiver 6000 has similar functionalityto receiver 104 of FIG. 1, and may be used within object tracking system100, FIG. 1, together with, or in place of, receivers 104. Optimizer 160is configured with antenna direction optimization software (illustratedbelow in FIGS. 62, 63, and 64) for remotely controlling direction (panand tilt) of antennae 6004 during operation of system 100.

In an alternate embodiment, receiver 104 is mounted on a remotecontrolled mount that has pan and tilt functionality, wherein pan andtilt of receiver 104 may be controlled to optimize performance of objecttracking system 100. For example, receiver 104 is mounted on a platformwith pan and tilt functionality that may be controlled from optimizer160 and optionally via receiver 104.

During installation of receivers 6000 for use with system 100, antenna6004 of each receiver 6000 is positioned at its neutral position (e.g.,mid-way in both pan and tilt motion) relative to receiver body 6002.Receivers 6000, as with receivers 104, are then each aligned to receivesignals from their assigned area of interest within operational area 102as evenly as possible. During operation of system 100, antennae 6004 arethen each individually positioned (using pan and tilt commands forexample) to optimize performance of system 100 based upon determinedsituations of interest (e.g., location of tags 101 of tag set 3512(1))within operational area 102. For example, each antenna 6004 may beadjusted such that receiver events 110 generated by pings 402 from tags101 associated with the situation of interest are maximized, therebyincreasing the likelihood that receiver 6000 will be involved inlocating these tags, increasing locate-to-ping ratio (e.g.,locate-to-ping ratio 4340, FIG. 43) within system 100, and therebyincrease data quality for those tags.

FIGS. 62, 63, and 64 are flowcharts illustrating one exemplary method6200 and sub-methods 6300, 6400 for optimizing performance of objecttracking system 100 by automatically and dynamically adjusting one orboth of pan and tilt of antennae 6004 to improve data quality determinedfrom tags 101 associated with a situation of interest. FIGS. 62, 63, and64 are best viewed together with the following description. Method 6200and sub-methods 6300 and 6400 are for example implemented withinoptimizer 160 of system 100, FIG. 1. In the following example, tag set3512(1) defines the situation of interest; however, any tag 101 or groupof tags may be used to define the situation of interest withoutdeparting from the scope hereof.

In step 6202, method 6200 determines receiver priority groups. In oneexample of step 6202, receiver event allocator 4302 determines receivergroups 4330 based upon the importance of each receiver 104 fordetermining locates of tags 101 identified within high priority tag set3512(1).

In step 6206, method 6200 selects a first receiver group. In one exampleof step 6206, optimizer 160 selects receiver group 4330(1), as shown inthe example of FIG. 47.

In step 6212, method 6200 invokes sub-method 6300 to adjust pan ofreceivers 6000 identified within the current receiver group. In step6214, method 6200 invokes sub-method 6400 to adjust tilt of receivers6000 identified within the current receiver group.

Step 6216 is a decision. If, in step 6216, method 6200 determines thatthe last receiver group has been processed, method 6200 terminates;otherwise method 6200 continues with step 6218. In step 6218, method6200 selects the next receiver group. In one example of step 6218,optimizer 160 selects receiver group 4330(2). Method 6200 then continueswith step 6212. Steps 6212 through 6218 repeat for each receiver group.

Pan Adjustment

In step 6302, sub-method 6300 selects a first receiver of the currentreceiver group. In one example of step 6302, optimizer 160 selectsreceiver 104(1) of receiver group 4330(1). In step 6303, sub-method 6300determines the current receiver pan angle. In one example of step 6303,optimizer 160 retrieves a stored value of antenna 6004 pan position ofreceiver 6000 that is set (a) during receiver initialization (e.g., wheneach receiver 6000 is set to zero degrees of pan and zero degree oftilt) and (b) when the position of antenna 6004 is updated (e.g.,position updates from step 6314).

In step 6304, sub-method 6300 determines a physical center of a regionbounding a tag set defining a situation of interest. In one example ofstep 6304, a center location of a smallest three dimensional polygonalshape containing all locations of tags 101 within tag set 3512(1) isdetermined. Step 6304 may occur immediately after step 6302 such thatthe physical center of the region bounding tag set 1 is determinedoutside of the loop formed by repeated steps 6303 through 6326.

Step 6306 is a decision. If, in step 6306, sub-method 6300 determinesthat the center of the situation of interest is left of the currentreceiver's aim, then sub-method 6300 continues with step 6308;otherwise, sub-method 6300 continues with step 6310. In step 6308,sub-method 6300 sets a pan direction to “left”. Sub-method 6300 thencontinues with step 6312. In step 6310, sub-method 6300 sets the pandirection to “right.”

In step 6312, sub-method 6300 determines a receiver-events-per-secondvalue for the tag set defining the situation of interest for the currentreceiver. In one example of step 6312, receiver event allocator 4302processes locate data 120 to determine a total count of receiver events110 associated with pings 402 of tags 101 identified within tag set3512(1) over a selected sample period for receiver 6000, and thencalculates the number of receiver events per second. In step 6314,sub-method 6300 commands the antenna 6004 of the current receiver to panfive degrees in the current pan direction. In one example of step 6314,optimizer 160 sends a command to receiver 6000 to pan antenna 6004 fivedegrees to the left. Other pan angle increments may be used withoutdeparting from the scope hereof. For example, step 6314 may pan antenna6004 one and a half degrees in the current pan direction. Step 6316 issimilar to step 6312, wherein sub-method 6300 determines a receiverevents per second value for the tag set defining the situation ofinterest for the current receiver.

Step 6318 is a decision. If, in step 6318, sub-method 6300 determinesthat the number of receiver events for the current receiver hasincreased, sub-method 6300 continues with step 6320; otherwise,sub-method 6300 continues with step 6322. In step 6322, sub-method 6300sets the antenna of the current receiver to the previous pan setting. Inone example of step 6322, optimizer 160 commands antenna 6004 ofreceiver 6000 to pan back five degrees. Sub-method 6300 then continueswith step 6326.

Step 6320 is a decision. If, in step 6320, sub-method 6300 determinesthat the antenna is at a maximum pan value, sub-method 6300 continueswith step 6326; otherwise, sub-method 6300 continues with step 6324.

Step 6324 is a decision. If, in step 6324 sub-method 6300 determinesthat the current receiver is the last receiver of the current receivergroup, sub-method 6300 returns control to method 6200; otherwise,sub-method 6300 continues with step 6326.

In step 6326, sub-method 6300 selects the next receiver of the currentreceiver group. In one example of step 6326, optimizer 160 selectsreceiver 104(3) of receiver group 4330(1). Sub-method 6300 thencontinues with step 6303. Steps 6303 through 6326 repeat for eachreceiver in the current receiver group, wherein pan of antenna 6004 ofeach receiver 6000 is adjusted to maximize receiver events per second atthe receiver for tags 101 within tag set 3512(1) that identify thesituation of interest.

Tilt Adjustment

In step 6402, sub-method 6400 selects a first receiver of the currentreceiver group. In one example of step 6402, optimizer 160 selectsreceiver 104(1) of receiver group 4330(1). In step 6403, sub-method 6400determines the current receiver tilt angle. In one example of step 6403,optimizer 160 retrieves a stored value of antenna 6004 tilt position ofreceiver 6000 that is set (a) during receiver initialization (e.g., wheneach receiver 6000 is set to zero degrees of pan and zero degree oftilt) and (b) when the position of antenna 6004 is updated (e.g.,position updates from step 6414).

In step 6404, sub-method 6400 determines a physical center of a regionbounding a tag set defining a situation of interest. In one example ofstep 6404, a center location of a smallest three dimensional polygonalshape containing all locations of tags 101 within tag set 3512(1) isdetermined. Step 6404 may occur immediately after step 6402 such thatthe physical center of the region bounding tag set 1 is determinedoutside of the loop formed by repeated steps 6403 through 6426.

Step 6406 is a decision. If, in step 6406, sub-method 6400 determinesthat the center of the situation of interest is above the currentreceiver's aim, then sub-method 6400 continues with step 6408;otherwise, sub-method 6400 continues with step 6410. In step 6408,sub-method 6400 sets a tilt direction to “down”. Sub-method 6400 thencontinues with step 6412. In step 6410, sub-method 6400 sets the tiltdirection to “up.”

In step 6412, sub-method 6400 determines a receiver-events-per-secondvalue for the tag set defining the situation of interest for the currentreceiver. In one example of step 6412, receiver event allocator 4302processes locate data 120 to determine a total count of receiver events110 associated with pings 402 of tags 101 identified within tag set3512(1) over a selected sample period for receiver 6000, and thencalculates the number of receiver events per second. In step 6414,sub-method 6400 commands the antenna 6004 of the current receiver totilt one degree in the current tilt direction. In one example of step6414, optimizer 160 sends a command to receiver 6000 to tilt antenna6004 one degree up. Other tilt angle increments may be used withoutdeparting from the scope hereof. For example, step 6414 may tilt antenna6004 one and a half decrees in the current tilt pan direction. Step 6416is similar to step 6412, wherein sub-method 6400 determines a receiverevents per second value for tags 101 within the tag set defining thesituation of interest for the current receiver.

Step 6418 is a decision. If, in step 6418, sub-method 6400 determinesthat the number of receiver events for the current receiver hasincreased, sub-method 6400 continues with step 6420; otherwise,sub-method 6400 continues with step 6422. In step 6422, sub-method 6400sets the antenna of the current receiver to the previous tilt setting.In one example of step 6422, optimizer 160 commands antenna 6004 ofreceiver 6000 to tilt back one degree. Sub-method 6400 then continueswith step 6426.

Step 6420 is a decision. If, in step 6420, sub-method 6400 determinesthat the antenna is at a maximum tilt value, sub-method 6400 continueswith step 6426; otherwise, sub-method 6400 continues with step 6424.

Step 6424 is a decision. If, in step 6424 sub-method 6400 determinesthat the current receiver is the last receiver of the current receivergroup, sub-method 6400 returned control to method 6200; otherwise,sub-method 6400 continues with step 6426.

In step 6426, sub-method 6400 selects the next receiver of the currentreceiver group. In one example of step 6426, optimizer 160 selectsreceiver 104(3) of receiver group 4330(1). Sub-method 6400 thencontinues with step 6403. Steps 6403 through 6426 repeat for eachreceiver in the current receiver group, wherein tilt of antenna 6004 ofeach receiver 6000 is adjusted to maximize receiver events per second atthe receiver for tags 101 within tag set 3512(1) that identify thesituation of interest.

Method 6200 and sub-methods 6300 and 6400 adjust antennae 6004 ofreceivers 6000 beginning with receivers of a high priority group (e.g.,receiver group 4330(1) that bound tags 101 of tag set 3512(1)), sincethese receivers are most likely to impact locate-to-ping ratio 4340 fortags associated with the situation of interest (e.g., tags 101 withintag set 3512(1)). The range of adjustment for panning antenna 6004 ismuch greater than the range for tilting antenna 6004 and panning is morelikely to increase the number of receiver events 110 associated withtags 101 of tag set 3512(1). Therefore, first pan is adjusted for allreceivers 6000 then tilt is adjusted for all receivers 6000.

Selectable Receiver Front-Ends

Although a sporting example is used within the following examples, othertypes of event and arena may be used without departing from the scopehereof.

FIG. 65 shows one exemplary scenario where an interferer 6570 interfereswith operation of system 100, FIG. 1. Object tracking system 100inevitably encounters environmental and/or situational changes that werenot present during installation of the system. For example, as shown inFIG. 65, interferer 6570 (e.g., a wireless camera) transmits a wirelesssignal 6572 that introduces changes in spectral content withinoperational area 102 that interferes with operation of object trackingsystem 100, particularly where wireless signal 6572 is at a frequencythat is at, or near, a center frequency of wireless signals detected byreceivers 104. Signal 6572 from interferer 6570 may be quite powerfulrelative to signal strength of ping 402 from tag 101, and interferer6570 may also be located nearer to one or more receivers 104 than tag101. Signal 6572 may therefore saturate sensitive front-end circuitry ofreceiver 104, thereby making the receiver unresponsive to pings 402 fromtags 101.

In the embodiment of FIG. 65, receivers 104 are dynamicallyconfigurable, under control of optimizer 160, to overcome environmentaland situational changes within operational area 102. For example,in-line frequency filtering circuitry, such as a band pass filter, maybe introduced, under control of optimizer 160, within receiver 104 toblock signal 6572 from saturating the sensitive analog circuitry (e.g.,detection electronics 606) of the receiver. Receiver 104 may alsobenefit from further front end adjustment to maintain optimalperformance of object tracking system 100. For example, where tag 101densities (e.g., the number of tags within a certain area) aredynamically shifting, receiver 104 may benefit from different antennaconfigurations that offer a variety of range and scope capabilities.

Optimizer 160, based upon locate data 120, dynamically determinesoptimal configuration for each receiver 104 and sends each receiver 104configuration data 170 to affect that optimal configuration.

Optimal configuration for each receiver 104 may be achieved byintroduction of a single component in the receiver's front-end. However,electronically switching analog components operating at the highfrequencies of UWB tags 101 is not practical because the analogcircuitry is extremely sensitive and switching of analog componentswould be disruptive to operation. To overcome this impracticality, theanalog circuitry is repeated for each desired analog configuration suchthat each receiver may have multiple self-contained analog front endsthat vary in their components (e.g. antennas and/or frequency filters)and that are switched into use by the receiver based upon desiredreceiver performance. Specifically, switching between multiple frontends is implemented digitally, thereby avoiding the impracticalities ofanalog switching.

FIG. 66 is a schematic showing a receiver 6604 for use with objecttracking system 100 of FIG. 1 and illustrating selectable differentfront ends 6626. Receiver 6604 may be used to implement any one or moreof receivers 104 of FIG. 1. FIGS. 67-69 show exemplary scope and rangecharacteristics of antennae 6602(1)-(3) of FIG. 66, respectively. FIGS.66-69 are best viewed together with the following description.

Receiver 6604 includes a digital switch 6634 positioned between adigital backend 6605 and a plurality of analog front ends 6626(1)-(3).Each analog front end 6626(1)-(3) includes a conditioning and convertingcircuitry 6606(1)-(3), and an antenna 6602(1)-(3), respectively, whereconditioning and converting circuitry 6606 is configured forconditioning an analog signal 6612 from antenna 6602 and converting theconditioned analog signal into a digital signal 6614 that is input todigital switch 6634.

Digital backend 6605 includes a receiver processor 6630, which receivesand decodes a digital signal 6616 from digital switch 6634, and aninterface 6632 for communicating with processing hub 150. For example,based upon decoded signal 6618, interface 6632 sends receiver event 110to processing hub 150. Interface 6632 may also receive configurationdata 170 from optimizer 160 (optionally via processing hub 150) andcontrol 6633 digital switch 6634 to select one of the analog front ends6626 based upon configuration data 170. Antennae 6602(1)-(3) each havedifferent scope and range characteristics.

Antenna 6602(1) is configured with characteristics 6700(1) that have along range 6702 (e.g., up to three-hundred and ninety feet) and a narrowscope 6704 (e.g., thirty degrees). Antenna 6602(2) is configured withcharacteristics 6700(2) that have a medium range 6802 (e.g., up totwo-hundred and ten feet) and a medium scope 6804 (e.g., ninetydegrees). Antenna 6602(3) is configured with characteristics 6700(3)that have a short range 6902 (e.g., up to one-hundred and twenty feet)and a wide scope 6904 (e.g., one-hundred and eighty degrees). Digitalswitch 6634 of receiver 6604 is controlled to select one analog frontend 6626 having optimum characteristics for current conditions.

Analog front end 6626(1) allows receiver 6604 to detect tags at thegreatest distance as compared to other analog front ends 6626(2) and(3). For example, when configured to receive information from analogfront end 6626(1), receiver 6604 may detect ping 402 from tag 101positioned at an opposite end of field of play 103 (e.g., an AmericanFootball playing field). This extended range comes at the expense ofscope, which is limited to thirty degrees in this example. Whenconfigured to receive information from front end 6626(3), receiver 6604may detect pings 402 from tag 101 when positioned anywhere across theentire width of field of play 103. However, this expanded scope comes atthe expense of range, which, in this example, is limited to a maximum ofone-hundred and twenty feet. Front end 6626(2) allows receiver 6604 todetect ping 402 from tag 101 within a range and scope that approximatelymidway between those of front ends 6626(1) and (3). Front end 6626(2) isthe default configuration for receiver 6604 and is for example usedduring initial installation of object tracking system 100, and likelyautomatically selected by optimizer 160 for use in the vast majority ofsituations.

Front ends 6626 may be configured with alternative characteristics 6700without departing from the scope hereof. For example, range and scope ofeach front end 6626 may be selected based upon the size and shape ofoperational area 102 and/or field of play 103. Further, not allreceivers 104 need be configured with that same number of front ends6626. For example, where receiver 6604 is positioned such that extendedrange is not required (e.g., where receiver is positioned at a sidelineof an American football field), front end 6626(1) having the longestrange 6702 may be omitted.

FIG. 70 is a schematic showing a receiver 7004 for use with the objecttracking system 100 of FIG. 1 and illustrating selectable front ends7026 with and without a filter 7050. Receiver 7004 may be used toimplement any one or more of receivers 104 of FIG. 1. Receiver 7004 issimilar to receiver 6604, FIG. 66, and common components of receiver7004 operate similarly to components of receiver 6604. Receiver 7004includes a digital switch 7002 positioned between a digital back end7005 and a plurality of analog front ends 7026(1)-(2). Digital backend7005 includes a receiver processor 7030, which receives and decodes adigital signal 7016 from digital switch 7002, and an interface 7032 forcommunicating with processing hub 150. For example, based upon decodedsignal 7018, interface 7032 sends receiver event 110 to processing hub150. Interface 7032 may also receive configuration data 170 fromoptimizer 160 (optionally via processing hub 150) and control 7033digital switch 7002 to select one of analog front ends 7026 based uponconfiguration data 170.

Each analog front end 7026(1)-(2) includes a conditioning and convertingcircuitry 7006(1)-(2), and an antenna 7002(1)-(2), respectively. Analogfront end 7026(1) is further configured with a filter 7050 positionedbetween antenna 7002(1) and conditioning and converting circuitry7006(1), wherein filter 7050 is configured to block frequencies ofsignal 6572 generated by interferer 6570, such that conditioning andconverting circuitry 7006(1) is not saturated by signal 6572.Frequencies of ping 402 are able to pass through filter 7050 and arethereby conditioned and converted by conditioning and convertingcircuitry 7006(1) to produce signal 614(1) containing information ofping 402. Filter 7050 is for example a six-point-five GHz(+/−two-hundred MHz) band pass filter. Band pass filters are notincluded within receivers by default since (a) they are expensive, (b)do not offer any value when interfering signals are not present, and (c)may unnecessarily attenuate pings when included and not needed.

Analog front end 7026(2) does not include a filter and antenna 610(2) isdirectly coupled with conditioning and converting circuitry 7006(2).Digital switch 7002 of receiver 7004 is controlled to select one analogfront end 7026 having optimum characteristics for current conditions.Front end 7026(2) does not block frequencies of signal 6572 and isthereby less optimal when signal 6572 is present within the environment.

Object tracking system 100 may be deployed with one or more receivers6604, 7004, each configured with digital switches 6634, 7034, andmultiple front-ends 6626, 7026, and with optimizer 160 thatautomatically configures each receiver to handle specific environmentalconditions and/or situational changes. Optimizer 160 and system 100 areeasier to install, more flexible over time, provide optimal performanceat all times, and result in object tracking that is far more faulttolerant than other systems that only have statically configuredreceivers.

EXAMPLES OF OPERATION Environmental Changes

Continuing with the example of FIG. 65, prior to operation of interferer6570 (e.g., a wireless broadcast camera), object tracking system 100 isoperating with optimal performance (i.e., processing hub 150 isreceiving an optimal number of receiver events 110 per second (RE/s))during an American Football game within operational area 102. When thewireless broadcast camera is activated, interferer 6570 startsgenerating wireless signal 6572 that immediately changes the environmentof object tracking system 100. For example, where signal 6572 has atransmission frequency of five-point-nine GHz and is transmitted at apower level of one watt, this is (a) only six-hundred MHz from thecenter operating frequency of six-point-five GHz of tag 101 andreceivers 104, and (b) at a power level of an order of magnitude greaterthan the milli-watt transmission power of tag 101. The analog circuitryof some or all receivers 104 becomes saturated by signal 6572, such thatone or more receivers 104 cannot detect ping 402. Thus, the number ofreceiver events 110 received and processed per second by processing hub150 immediately drops to a sub-optimal level, such as fromtwelve-hundred RE/s to two-hundred RE/s, such that location of tag 101fails.

Within optimizer 160, the RE/s value is monitored during operation ofsystem 100. When the RE/s value drops to a sub-optimal level (e.g.,two-hundred RE/s), system 100 may attempt to employ other techniques toincrease RE/s. However, where the environmental change is serious, suchas with interferer 6570, these other techniques cannot restoreoperability of object tracking system 100, resulting in catastrophicloss of locates within locate data 120. Occurrence of such catastrophicfailure indicates a significant change in the environment, such as theintroduction of one or more interferers.

Optimizer 160 operates to configure characteristics of one or morereceivers 7004 to filter out the effects of signal 6572. For example,optimizer 160 may send configuration data 170 to interface 7032, whichcontrols digital switch 7002 to select signal 7014(1) from front end7026(1) for input to digital back-end 7005, such that interference bysignal 6572 is reduced.

FIG. 71 is a flowchart illustrating one exemplary method 7100 forautomatic object tracking system optimization based upon environmentalchanges. Method 7100 is for example implemented within software 162 ofoptimizer 160, FIG. 1, and is invoked periodically for each receiver7004 within object tracking system 100.

In step 7102, method 7100 calculates RE/s. In one example of step 7102,optimizer 160 calculates RE/s 4310 for receiver 7004 to be two-hundred.Step 7104 is a decision. If, in step 7104, method 7100 determines thatRE/s is within operational limits, method 7100 terminates; otherwisemethod 7100 continues with step 7106. In one example of step 7104,optimizer 160 determines the two-hundred RE/s 4310 of receiver 7004 isnot within operational limits and continues with step 7106.

Step 7106 is a decision. If, in step 7106, method 7100 determines thatthe front end with filter is already selected, method 7100 continueswith step 7114; otherwise, method 7100 continues with step 7108. In oneexample of step 7106, optimizer 160 determines that front end 7026(2)without filter 7050 is selected for receiver 7004 from receiverconfiguration information 6552 and continues with step 7108. In step7108, method 7100 switches the receiver to use the front end with thefilter. In one example of step 7108, optimizer 160 sends configurationdata 170 to receiver 7004, wherein interface 7032 controls digitalswitch 7034 to select analog front-end 7026(1) that contains filter7050.

In step 7110, method 7100 calculates RE/s for the receiver. In oneexample of step 7110, optimizer 160 calculates RE/s 4310 for receiver7004 to be one-thousand. Step 7112 is a decision. If, in step 7112,method 7100 determines that RE/s is within limits, method 7100terminates; otherwise method 7100 continues with step 7114.

In step 7114, method 7100 displays an error indicating that thesub-optimal RE/s cannot be optimized. In one example of step 7114,optimizer 160 sends a message to an operator of system 100 indicatingthat RE/s cannot be returned to operational limits for the receiver.Method 7100 then terminates. Once analog front-end 6626(1) (implementingfilter 7050) is selected, it remains selected until the system isreinitialized (e.g., until the end of the current event).

Situational Changes

FIG. 72 shows exemplary positioning of receiver 6604 at one end of fieldof play 103 (e.g., an American Football field) and illustratingselection of one analog front end 6626 based upon situational changes.Only one receiver 6604 is shown for clarity of illustration. As shown inFIGS. 66-69, receiver 6604 is configured with three analog front ends6626(1)-(3) that have characteristics 6700(1)-(3), respectively.Characteristics 6700 are selected based upon operational area 102 andthe intended activity of tracked objects (e.g., athletes) therein. Inthe example of FIG. 72, field of play 103 is an American Football fieldand expected activity is an American Football game. Receiver 6604operating with front end 6626(1) selected has an exemplary receive area7220 (indicated by dashed outline). Receiver 6604 operating with frontend 6626(2) selected has an exemplary receive area 7222 (indicated bydashed outline). Receiver 6604 operating with front end 6626(3) selectedhas an exemplary receive area 7224 (indicated by dashed outline).

Locations of players 7202 of a first team are indicated by Xs andlocations of players 7204 of a second team are indicated by Os. Eachplayer 7202, 7204 is configured with at least one tag 101 that allowsobject tracking system 100 to determine at least the location of eachplayer.

Optimizer 160 operates to automatically select an appropriate front end6626 for receiver 6604 based upon determined locations of certainplayers 7202, 7204 within operational area 102. For example, optimizer160 may send configuration data 170 to interface 6632, which controlsdigital switch 6634 to select signal 6614 from one of front ends 6626for input to digital back-end 6605 based upon determined situationalchanges. In particular, optimizer 160 selects one of front end 6626based upon location of players of interest, which, for the exemplaryAmerican Football game, are the players located on field of play 103 andactively participating in the game. Optimizer 160 first determines abounding rectangle 7210, aligned to field of play 103 for example, thatincludes determined locations of RF tags 101 for players of interest.Based upon the location of the perimeter of bounding rectangle 7210relative to receiver 6604, optimizer 160 selects an appropriate frontend 6626. In the example of FIG. 72, optimizer 160 selects front end6626(1) for receiver 6604 since bounding rectangle 7210 is withinreceive area 7220 and not within receive areas 7222 and 7224.

FIG. 73 is similar to FIG. 72 and shows progress of play in theexemplary American Football game on field of play 103, wherein boundingrectangle 7210 has moved relative to receiver 6604. Optimizer 160repeatedly recalculates bounding rectangle 7210 and determines optimalconfiguration for each receiver 6604 as play progresses on field of play103. Optimizer 160 then sends configuration data 170 to interface 6632,which controls digital switch 6634 to select signal 6614 from one offront ends 6626 for input to digital back-end 6605 based upon determinedsituational changes. In the example of FIG. 73, bounding rectangle 7210is better covered by receive area 7222, since extended range is nolonger required and increased scope provides better coverage of boundingrectangle 7210. Therefore, optimizer 160 automatically controls receiver6604 to use front end 6626(2).

As play progresses and bounding rectangle 7210 becomes even closer toreceiver 6604, optimizer 160, based upon receive area 7224 and boundingrectangle 7210, may automatically control receiver 6604 to use front end6626(3), since receiver 6604 achieves better performance using a LowGain antenna, which provides maximum scope at the expense of range.

Optimizer 160 periodically determines bounding rectangle 7210, and thenfor each receiver 6604 of object tracking system 100, determines anappropriate front end 6626 for use based upon the orientation andlocation of each receiver 6604.

FIG. 74 is a flowchart illustrating one exemplary method 7400 forautomatic object tracking system optimization based upon environmentalchanges. Method 7400 is for example implemented within optimizer 160,FIG. 1. In step 7402, method 7400 selects a first receiver 6604 ofobject tracking system 100. In one example of step 7402, optimizer 160selects receiver 104(1), implemented with receiver 6604. In subsequentiterations of step 7402, method 7400 selects a next receiver 6604 ofobject tracking system 100.

In step 7404, method 7400 determines a bounding rectangle for RF tags ofinterest. In one example of step 7404, optimizer 160 determines boundingrectangle 7210 for RF tags 101 of players participating on field of play103. In step 7406, method 7400 looks up configuration information forthe current receiver. In one example of step 7406, optimizer 160retrieves receiver configuration information 6552 for receiver 104(1) todetermine one or more of location, orientation, and configurability ofreceiver 104(1).

Step 7408 is a decision. If, in step 7408, method 7400 determines, basedupon the bounding rectangle determined in step 7404 and the receiverconfiguration determined in step 7406, that a front end with maximumrange is optimal for the receiver, method 7400 continues with step 7410.If, in step 7408, method 7400 determines, based upon the boundingrectangle determined in step 7404 and the current receiver configurationdetermined in step 7406, that a front end with medium range and mediumscope is optimal for the current receiver, method 7400 continues withstep 7412. If, in step 7408, method 7400 determines, based upon thebounding rectangle determined in step 7404 and the current receiverconfiguration determined in step 7406, that a front end with maximumscope is optimal for the current receiver, method 7400 continues withstep 7414. In one example of step 7408, for a receiver 6604 positionedcentrally at one end of field of play 103 (as shown in FIGS. 72 and 73),where optimizer 160 determines that bounding rectangle 7210 is beyondthe fifty-yard line (as shown in FIG. 72), optimizer 160 continues withstep 7410. In another example of step 7408, where optimizer 160determines that bounding rectangle 7210 is between the fifty-yard lineand beyond the fifteen-yard line (as shown in FIG. 73), optimizer 160continues with step 7412. In another example of step 7408, whereoptimizer 160 determines that bounding rectangle 7210 is closer than thefifteen-yard line, optimizer 160 continues with step 7414.

In step 7410, method 7400 controls the current receiver to switch to themaximum range front end. In one example of step 7410, optimizer 160sends configuration data 170 to receiver 104(1)/6604, instructinginterface 6632 to control digital switch 6634 to select front end6626(1). Method 7400 then continues with step 7416.

In step 7412, method 7400 controls the current receiver to switch to themedium range and medium scope front end. In one example of step 7412,optimizer 160 sends configuration data 170 to receiver 104(1)/6604,instructing interface 6632 to control digital switch 6634 to selectfront end 6626(2). Method 7400 then continues with step 7416.

In step 7414, method 7400 controls the current receiver to switch to themaximum scope front end. In one example of step 7414, optimizer 160sends configuration data 170 to receiver 104(1)/6604, instructinginterface 6632 to control digital switch 6634 to select front end6626(3). Method 7400 then continues with step 7416.

Step 7416 is a decision. If, in step 7416, method 7400 determines thatthe current receiver is not the last receiver, method 7400 continueswith step 7402; otherwise, method 7400 terminates. Steps 7402 through7416 thereby repeat for each receiver 104/6604, of object trackingsystem 100.

Post-Locate Filter Adjustments

Under extreme conditions (e.g. receiver failure, cable failure,torrential rain and other adverse weather conditions), even with allavailable receivers 104 configured with a maximum gain value (e.g.,one-hundred percent), the locate-to-ping ratio (e.g., locate-to-pingration 4340) of system 100 may fail to reach the target range (e.g.,55%). Under these extreme conditions, system 100 may not generatesufficient locates, resulting in non-contiguous tracking data (i.e.,where gaps appear in tracking movements).

FIG. 75 shows system 100 of FIG. 1 determining locates of tags101(1)-(3) within operational area 102, where the calculated locatespass through an array of filter algorithms within processing hub 150.These filtering algorithms include a data convergence filter 7510, abounding box filter 7512, and a receiver count filter 7516. A threshold7511 controls operation of data convergence filter 7510; a threereceiver threshold 7513 and a four receiver threshold 7515 controloperation of bounding box filter 7512; and a three locate enable 7517controls operation of receiver count filter 7516.

In general, contiguous tracking data with reduced overall accuracy isfar more valuable to applications 130 that use this information thannon-contiguous data with higher accuracy (i.e., where system 100 isconfigured to filter out locates with reduced accuracy). In normaloperation of system 100, reduced accuracy locates are filtered out oflocate data 120 by post-locate filters such as data convergence filter7510, bounding box filter 7512, and receiver count filter 7516. However,when system 100 fails to generate sufficient locates, a filtercontroller 7502 within optimizer 160 operates to automatically adjustcontrolling parameters (e.g., thresholds 7511, 7513 and 7515, and threelocate enable 7517) of one or more post locate filters (e.g., dataconvergence filter 7510, bounding box filter 7512, and receiver countfilter 7516) to increase tolerance within these filters to allow morelocates to be output within locate data 120 at the expense of accuracyof those generated locates.

The reliability level of locates varies depending on a number ofdifferent factors. There are various methods of estimating thereliability level of locates, as discussed below. Within processing hub150, generated locates pass through an array of filtering algorithms.These filtering algorithms fall into two general categories: (a) signalprocessing and (b) identify & drop. Dynamic optimization is performedonly for (b) identify & drop algorithms such as data convergence filter7510, bounding box filter 7512, and receiver count filter 7516, whichoperate to evaluate several attributes of each locate to estimate itsreliability. If the estimated reliability of the locate is below aspecified threshold in any of these, then the locate is discarded toreduce the number of locates generated by system 100 in favor of higherreliability locates.

Where all receivers 104 are operating at maximum gain and locate-to-pingratio 4340 of system 100 is still insufficient, filter controller 7502within optimizer 160 automatically adjusts thresholds 7511, 7513 and7515, and three locate enable 7517 of data convergence filter 7510,bounding box filter 7512, and receiver count filter 7516, respectively,to achieve an acceptable locate-to-ping ratio 4340. These adjustmentsare made at the expense of generating locates with less reliablelocation information and of thereby potentially reducing overallaccuracy of system 100. The rationale for this is that oncelocate-to-ping ratio 4340 falls below a certain level, gaps in locatedata 120 represent a more serious problem than does a decrease inaverage system accuracy.

Data convergence filter 7510, bounding box filter 7512, and receivercount filter 7516 are examples of identify and drop algorithms. Otheridentify and drop algorithms may be included within processing hub 150and automatically controlled by filter controller 7502 without departingfrom the scope hereof.

Data Convergence Filter

When more than three receiver events 110 result from the same ping 402and are used to determine a locate, processing hub 150 determines a dataconvergence estimate for the locate based upon difference in calculatedlocations for each different set of three receiver events. The greaterthe convergence in (e.g., the smaller the average distance between) thecalculated locations, the more likely the calculated location isaccurate. Data convergence filter 7510 discards data when the dataconvergence estimate is above threshold 7511. Filter controller 7502operates to increase threshold 7511 when the locate-to-ping ratio 4340of system 100 is low, which increases the number of locates generated bysystem 100, since fewer locates are discarded due to inaccuracy.Similarly, filter controller 7502 decreases threshold 7511 whenlocate-to-ping ratio 4340 of system 100 is greater than a desired value(e.g., above fifty-five percent) to reduce the number of locatesgenerated.

Bounding Box Filter

A bounding box is the smallest polygon that includes all receivers 104involved in calculating a particular locate. For any locate calculation,a bounding box for that locate is formed by drawing a line between allreceivers involved in the calculation. For example, FIG. 26 shows athree receiver bounding box 7522 formed by receivers 104(1),104 (2) and104(11) that each generated one receiver event 110 used to calculate thelocation of tag 101(1). Similarly, a four receiver bounding box 7524 isformed by receivers 104(2), 104(3), 104(9), and 104(10) that eachgenerated one receive event 110 used to calculate the location of tag101(2). Similarly again, a five receiver bounding box 7526 is formed byreceivers 104(3), 104(5), 104(6), 104(7), and 104(8) that each generatedone receiver event 110 used to calculate the location of tag 101(3). Inthe example of FIG. 75, the locate of tag 101(1) is within bounding box7522, but is very close to the boundary; the locate of tag 101(2) isoutside the boundary of bounding box 7524; and the locate of tag 101(3)is well inside the boundary of bounding box 7526.

As the calculated location approaches the edge of the bounding box, thereliability of the calculated location (i.e., the locate) decreases. Ifthe calculated location is outside the bounding box (e.g., locate of tag101(2) is outside bounding box 7524), the reliability of the calculatedlocation (i.e., the locate) decreases even further. The further thecalculated location is outside the bounding box, the lower thereliability of that locate. Bounding box filter 7512 operates todiscards locates where the calculated location is outside the boundaryof the bounding box (e.g., one of bounding boxes 7522, 7524, 7526). Forexample, locates having calculated locations within the bounding box(e.g., bounding boxes 7522, 7524, 7526) defined by the receivers used todetermine the locate are output within locate data 120, whereas locateswith calculated locations outside of the bounding boxes are discarded.

The size of the bounding boxes may be adjusted by thresholds (e.g.,three receiver threshold 7513 and four receiver threshold 7515) thatincrease the size of the bounding box when positive and decrease thesize of the bounding box when negative. These thresholds are angularadjustments relative to the straight lines between receiver pairs. FIG.78 is a schematic showing one exemplary bounding box 7802 for threereceivers 104(1), 104(2), 104(3) where three receiver threshold 7513 isa positive value. FIG. 79 is a schematic showing one exemplary boundingbox 7902 for three receivers 104(1), 104(2), 104(3) where three receiverthreshold 7513 is negative. FIG. 80 is a schematic showing one exemplarybounding box 8002 for four receivers 104(1), 104(2), 104(3), 104(4)where four receiver threshold 7515 is a positive value. FIG. 81 is aschematic showing one exemplary bounding box 8102 for four receivers104(1), 104(2), 104(3), 104(4) where four receiver threshold 7515 is anegative value.

Bounding box filter 7512 operates in two modes: a three receiver locatemode and a four receiver locate mode (which uses four or morereceivers). In the four receiver locate mode, where the number ofreceiver events 110 used to determine a locate is greater than three,bounding box filter 7512 uses four receiver threshold 7515 to define thebounding box (e.g., bounding box 8002, 8102) and thereby determinewhether the locate should be discarded. In three receiver locate mode,where the number of receiver events 110 used to determine a locate isthree, bounding box filter 7512 uses three receiver threshold 7513 todefine the bounding box (e.g., bounding box 7802, 7902) and therebydetermine whether the locate should be discarded. All three receiverlocates, regardless of the bounding box setting, are gated by the“Receiver Count Filter.” Three receiver threshold 7513 is typically settighter than four receiver threshold 7515, since convergence informationfor a locate is not available when only three receiver events 110 areused to calculate the locate and thus data convergence filter 7510cannot be used.

As described below, and shown in FIGs.76 and 77, operation of boundingbox filter 7512 is controlled using three receiver threshold 7513 andfour receiver threshold 7515. Both thresholds 7513 and 7515 have adefault value of zero, a lower limit of minus-thirty, and an upper limitof plus-thirty. Each may also have a default increment/decrement amountof five.

Receiver Count Filter

During normal operation of system 100, three locate enable 7517 is setto false and receiver count filter 7516 operates to discard locatesdetermined from only three receiver events 110 since no data convergenceestimate is available for that locate. However, where system 100 isoperating below the defined locate-to-ping ratio (e.g., fifty-fivepercent), three locate enable 7517 is set to true by filter controller7502 such that receiver count filter 7516 does not discard locatesgenerated from only three receiver events 110.

Post-Locate Filter Adjustment Process

When locate-to-ping ratio 4340 falls below a defined target threshold,optimizer 160 adjusts one or more post-locate filters to increase thenumber of receiver events 110 and thereby improve locate-to-ping ratio4340. The specific parameter adjustment algorithm employed withinoptimizer 160 is selected based upon the condition, or conditions,responsible for the reduced locate-to-ping ratio.

FIGS. 76 and 77 show one exemplary generic method 7600 for automaticallyadjusting post-locate filters within processing hub 150 based uponlocate-to-ping ratio 4340 of system 100. Method 7600 is implementedwithin filter controller 7502 of optimizer 160 and invoked periodicallyto manage post-locate filters for example.

In step 7602, method 7600 calculates a locate-to-ping ratio for system100. In one example of step 7602, filter controller 7502 determines alocate-to-ping ratio for system 100.

Step 7604 is a decision. If, in step 7604, method 7600 determines thatthe locate-to-ping ration is high, method 7600 continues with step 7606;otherwise method 7600 continues with step 7610. In step 7606, method7600 disables three receiver locates. In one example of step 7606,filter controller 7502 sets three locate enable 7517 to false, whereuponreceiver count filter 7516 discards locates generated from only threereceiver events 110. In step 7608, method 7600 resets data convergenceand bounding box thresholds. In one example of step 7608, filtercontroller 7502 resets threshold 7511 to a value representative ofnormal operation of system 100, and sets thresholds 7513 and 7515 tozero. Method 7600 then terminates.

Step 7610 is a decision. If, in step 7610, method 7600 determines thatthe locate-to-ping rate is too low, method 7600 continues with step7612; otherwise method 7600 terminates.

Step 7612 is a decision. If, in step 7610, method 7600 determines thatthe data convergence filter is at the limit, method 7600 continues withstep 7616; otherwise method 7600 continues with step 7614. In step 7614,method 7600 increases the convergence threshold. In one example of step7614, filter controller 7502 increases threshold 7511 such that fewerlocates are discarded due to poor accuracy. Method 7600 then continueswith step 7602.

Step 7616 is a decision. If, in step 7616, method 7600 determines thatthe receiver bounding box filter is at its limit, method 7600 continueswith step 7620; otherwise method 7600 continues with step 7618. In step7618, method 7600 increases the bounding box filter four receiverthreshold by a predefined amount. In one example of step 7618, filtercontroller 7502 increases the value of four receiver threshold 7515 byfive such that the area of the defined bounding box is increased forbounding box filter 7512. Method 7600 then continues with step 7602.Steps 7602 through 7618 repeat to control locate-to-ping ratio 4340 ofsystem 100 by increasing first the data convergence filter threshold andthen the bounding box filter convergence adjustment to increasetolerance in accuracy of the calculated location of locates.

In step 7620, method 7600 sets the three receiver bounding box parameterto a negative limit. In one example of step 7620, filter controller 7502sets three receiver threshold 7513 to minus thirty to reduce the size ofthe bounding box, wherein locates that are not within the bounding boxare discarded.

In step 7622, method 7600 allows three receiver locates. In one exampleof step 7622, filter controller 7502 sets three locate enable 7517 totrue, thereby preventing receiver count filter 7516 from rejectinglocates generated from only three receiver events 110.

In step 7624, method 7600 calculates the locate-to-ping ratio. In oneexample of step 7624, filter controller 7502 calculates locate-to-pingratio 4340 based upon, for a defined period, expected pings 402 fromtags 101 and a count of generated locates within locate data 120.

Step 7626 is a decision. If, in step 7626, method 7600 determines thatthe locate-to-ping ratio is high, method 7600 continues with step 7628;otherwise method 7600 continues with step 7632. In step 7628, method7600 disables three receiver locates. In one example of step 7628,filter controller 7502 sets three locate enable 7517 to false, therebyallowing receiver count filter 7516 to discard locates calculated fromonly three receiver events 110. In step 7630, method 7600 resets dataconvergence and bounding box parameters. In one example of step 7630,filter controller 7502 sets threshold 7511 to a default value definingnormal operation of data convergence filter 7510, and sets thresholds7513 and 7515 to a default values defining normal operation of boundingbox filter 7512. Method 7600 then terminates.

Step 7632 is a decision. If, in step 7632, method 7600 determines thatthe locate-to-ping ration is low, method 7600 terminates; otherwisemethod 7600 continues with step 7634.

Step 7634 is a decision. If, in step 7634, method 7600 determines thatthe bounding box parameters are at a limit, method 7600 continues withstep 7638; otherwise method 7600 continues with step 7636. In step 7636,method 7600 increases the bounding box parameters by a predefinedamount. In one example of step 7636, filter controller 7502 increaseseach of thresholds 7513 and 7515 by five. Method 7600 then continueswith step 7624. Steps 7624 through 7636 repeat to continually monitorand control the locate-to-ping ratio 4340 of system 100 by adjustingthree locate parameters of bounding box filter 7512 to increase the areain which calculated locations are not rejected.

In step 7638, method 7600 generates a system warning. In one example ofstep 7638, filter controller 7502 generates a warning message indicatingthat the desired locate-to-ping ratio cannot be achieved for display toone or more operators of system 100. Method 7600 then terminates.

As noted above, method 7600 is a generic control algorithm for clarityof illustration. Other potentially more advanced control algorithms maybe implemented within filter controller 7502 to control operation ofdata convergence filter 7510, bounding box filter 7512 and receivercount filter 7516 without departing from the scope hereof.

In summary, when locate-to-ping ratio 4340 decreases below a predefinedthreshold, method 7600 incrementally increases threshold 7511 of dataconvergence filter 7510 until it reaches a predefined limit (i.e.,maximum value). Data convergence filter 7510 is adjusted first sincethis allows more locates to be generated that are directly tied to acalculated reliability metric. Although the overall accuracy of system100 is impacted by allowing generating locates with higher dataconvergence values, the potential inaccuracy of these locates areintroduced in a controlled manner. Where adjustment to threshold 7511 ofdata convergence filter 7510 fails to increase locate-to-ping ratio 4340to a sufficient level, filter controller 7502 then incrementally makespositive adjustments to four receiver threshold 7515 of bounding boxfilter 7512, where each increase in the value of four receiver threshold7515 increases the area within which calculated locations are notdiscarded by bounding box filter 7512. Although calculated locations ofeach locate may be outside their bounding box, and therefore have aninherently higher level of inaccuracy, these locates have not beendiscarded by data convergence filter 7510, and therefore have apre-defined acceptable data convergence measure.

If a predefined maximum value for four receiver threshold 7515 isreached and the locate-to-ping ratio 4340 is still not at a sufficientlevel, filter controller 7502 then initiates more drastic measures toincrease the locate-to-ping ratio by allowing locates to be generatedfrom three receiver events (i.e., three different receivers). As notedabove, when calculating location using only three receiver events 110, adata convergence value cannot be used to estimate reliability and/oraccuracy of the locate. Thus, for locates generated using only threereceiver events, three receiver threshold 7513 is set to have a smaller(i.e., tighter) area for accepting locates within bounding box filter7512. Therefore, the three receiver threshold 7513 is initially set toits most negative value, corresponding to its smallest area (i.e.,tightest setting). This area is then gradually increased until anacceptable locate-to-ping ratio 4340 is achieved.

Where filter controller 7502 is still unable to achieve a satisfactorylocate-to-ping ratio 4340, a system warning is generated to indicatethat the locate-to-ping ratio is low and that gaps in data may result.By generating this warning, filter controller 7502 alerts an operator ofsystem 100 to potential problems or faults within system 100.

Where reduced locate-to-ping ratio is a result of a condition such asextreme weather or a disconnected cable for example, the condition mayrapidly disappear, such as when weather improves or the cable isreconnected. When the condition disappears, filter controller 7502detects the increase in locate-to-ping ratio 4340 and automaticallyreconfigures one or more of data convergence filter 7510, bounding boxfilter 7512, and receiver count filter 7516 for normal operation byresetting one or more of thresholds 7511, 7513, 7515, and three locateenable 7517 to default values for normal operation of object trackingsystem 100.

Location Data Visualization Tools

FIG. 82 shows processing hub 150 of system 100, FIG. 1 communicativelycoupled with a database 8203, a playback tool 8202, and an analysis tool8208. Tool 8208 may operate with live data from processing hub 150(i.e., as tags 101 are tracked within operational area 102); however,tool 8208 more usefully processes recorded data 8204 that includes tagIDs 208, receiver IDs (e.g., receiver ID 714) of receivers 104 involvedin both successful and failed locates, errors, and other informationfrom receivers 104 as stored in database 8203. For example, duringoperation of system 100, receiver events 110, errors, receiver listdata, and other information (e.g., type of data (successful/unsuccessfullocate), Tag ID, xyz data, error code, indication of data quality, and alist of involved receivers 104 in determining the locate) are stored asrecorded data 8204 within database 8203. Playback tool 8202 communicateswith database 8203 and processing hub 150 to replay, through processinghub 150, both successful and unsuccessful locates and other informationfrom receivers 104 stored within database 8203. Playback tool 8202 mayrepeatedly “replay” a portion of recorded data 8204 so that parameters(e.g., filtering) within processing hub 150 and locate algorithms 152may be adjusted, permitting a system administrator to enhanceperformance of system 100 for a particular environment. Playback tool8202 also allows a user to view alternative aspects of the data, and toanalyze different portions of the playing field on a graphicalrepresentation (e.g., generated by application 130) of the recordedevent.

Playback tool 8202 may replay recorded data 8204 at the captured rate(i.e., replicating the exact conditions as they were when the data wascollected). However, playback tool 8202 may also replay recorded data8204 at other speeds; for example recorded data 8204 may be replayed asfast as other components of system 100 will allow, which is typicallymany times the recording speed. In one example of operation, playbacktool 8202 is used to repeatedly replay at least a portion of recordeddata 8204 at high speed when iteratively tuning and/or troubleshooting aproblem with system 100.

When configuring system 100 at a new installation (i.e., a new sportingvenue), one useful data set is a “Test Lap”. In a Test Lap, a single tag101 is moved methodically within operational area 102. For example, aperson wears a hat that includes tag 101 and walks a grid pattern overfield of play 103 within operational area 102. System 100 storesrecorded data 8204 during the test lap such that playback tool 8202 mayreplay the data, through processing hub 150, into analysis tool 8208.During the test lap, system 100 is operating with ideal conditions,where tag 101 is approximately 2 meters off the ground, positioned in ahorizontal plane, and has clear unobstructed lines of sight to allreceivers 104 positioned around operational area 102.

Analysis tool 8208 incorporates one or more software modules thatinclude machine readable instructions that, when executed by a processorof a computer, implement functionality described below. In oneembodiment, analysis tool 8208 is implemented as a separate,communicatively connected (e.g., networked), computer from processinghub 150. Analysis tool 8208 may operate with any type of data withinrecorded data 8204, but is particularly useful when recorded data 8204contains information recorded from a test lap. For example, whererecorded data 8204 contains a single test lap data set, analysis tool8208 provides for analyzing a wide variety of different types ofproblems with the installation calibration and filter adjustments ofsystem 100.

FIG. 83 shows one exemplary static line plot 8300 generated by a staticline plotter 8210 of analysis tool 8208. Static line plot 8300 is forexample generated from determined locations (locates 8209 within locatedata 120) of tag 101 during replay of recorded data 8204. Within plot8300, static line plotter 8210 displays each determined locate 8209 oftag 101 as a symbol 8302 on a visual representation of operational area102, such that all locates 8209 are displayed simultaneously. (Othertypical tracking displays show only a moving point representing thelocation of a tracking tag at any one point in time.) In the example ofFIG. 83, symbol 8302 is a yellow circle representing the position ofeach locate 8209 within an American football field (field of play 103)within operational area 102. Although plot 8300 shows an area 8304 wheretracking information appears to be missing, the majority of the displayappears to be visually correct. For example, it's only when a largenumber of consecutive errors occur that a sudden jump in the reportedposition becomes visible. Even when such gaps are visible, there is noindication of what type of problem caused the gap in reported positions.In system 100, processing hub 150 may implement many types of filtersthat condition the received data and that may indicate many distincterror conditions that may cause the determination of the location of tag101 to fail.

FIG. 84 shows one exemplary enhanced static line plot 8400 that furthercombines additional error and receiver information from recorded data8204 with the plotted symbols 8302 that represent determined locates8209. Often, since test lap data is generated and collected under idealconditions, what appears to be minor issues in test lap data mayactually indicate bigger problems that will manifest at those same fieldlocations during “game day” conditions. The “game day” environment isfar more demanding than a test lap since tag transmissions may bepartially blocked by nearby athletes.

Static line plotter 8210 also generates and plots symbols that visuallyrepresent errors occurring within system 100, even errors that would notbe noticeable during normal operation of system 100. Plotter 8210visually displays these errors and other information on plot 8400 assymbols positioned to represent the location of tag 101 when the errorand/or information occurred. Plot 8400 thereby provides a method ofdistinguishing between different types of error conditions andinformation that occurs within system 100. Most importantly, plot 8400relates error conditions to the position within tracking area 100 (i.e.,on field of play 103) where they occurred.

Plotter 8210 displays a symbol even when no valid locate 8209 has beendetermined. In that case, plotter 8210 plots a symbol at the last knowntag location and in a different color to represent the type of error.For example, each error condition (e.g. too few receivers, noconvergence, etc.) is color coded, as represented by letters shown inFIG. 84. In the example of FIG. 84, letters positioned on the symbolsindicate a color corresponding to data type selections of FIG. 85,described below.

Where a single error occurs between two locates 8209 (i.e., validlocation determinations), the plotted symbol is the same size as thesymbol plotted for a locate. Where more than one (‘n’) consecutive pings402 result in the same error, the size of the plotted symbol increasesproportional to ‘n’. Thus, the greater the number of consecutive,recurring errors of the same type, the more visibly noticeable theplotted symbol.

Plot 8400 allows errors associated with a specific location withinoperational area 102 to be immediately apparent. For example, as tag 101crosses the problem area within operational area 102, that area withinplot 8400 turns a color consistent with the error type, and where theerror persists for consecutive pings 402, that area within plot 8400“blooms” into a large color coded visual representation 8402.

As shown in plot 8400, a large number of errors occurred during replayof recorded data 8204 (i.e., the test lap data set). Nearly all of theseerrors are invisible when viewed using plot 8300 of FIG. 83. Inparticular, plot 8400 visually indicates 8404 exactly where an erroroccurred, why it occurred, and how frequently it occurred. Easyassimilation of this information by a system administrator (or installengineer) is crucial when initially configuring system 100 within a newenvironment, and for adjusting all of the possible filtering algorithmswithin processing hub 150.

Playback tool 8202 may be used to repeatedly replay recorded data 8204at high speed and generate plot 8400 with modified filter parameters.With each adjustment, the administrator sees the effect on theadjustments on the test lap data set. This provides a fast and visibleway of initially “tuning” system 100.

FIG. 85 shows one exemplary dialog box 8500 for selecting features forinclusion within plot 8400, wherein each feature is color coded (asrepresented by the letters, such a C-Cyan, M-Magenta, O-orange, and soon.). For example, a user may select the type of error to be displayedwithin plot 8400, wherein the symbol is displayed on plot 8400 in theassociated color. Even where plot 8400 represents a short period, alarge number of individual tags 101 and tens or hundreds of thousands ofindividual locates 8209 may be included. Plotter 8210 provides a veryquick and simple way to visually identify a problem in a sea of data.However, when diagnosing a cause of the problem, it is nearly alwaysnecessary to look at a relatively small amount of data associated with asingle tag 101, immediately before and after the error occurred.

FIG. 86 shows a portion 8600 of recorded data 8204 selected by a visualdata selector 8212 within analysis tool 8208. In particular, selector8212 cooperates with plotter 8210 and plot 8400 to select the portion ofrecorded data 8204 based upon the user clicking with a mouse on plot8400. In one embodiment, analysis tool 8208 stores a copy of allinformation used to generate plot 8400, together with an identifier(TagID) of tag 101. Selector 8212 finds the nearest plotted point to theclick location on plot 8400, determines the TagID of that plotted point,and then retrieves n number of the underlying data samples for thatTagID, from both immediately before/after the nearest plotted point.

Thus, the combination of plotter 8210 and selector 8212 provides apowerful tool for quickly looking deeply into the lowest level data toease identification of system problems and diagnosing their causes. Thiscombination is also valuable for adjusting the many different types offilters that may potentially be part of system 100, and gettingimmediate visual feedback corresponding to each adjustment.

In a typical installation of system 100, anywhere from 4-12 receivers104 are arranged around operational area 102. To ensure complete andreliable coverage of operational area 102, ping 402 from tag 101,positioned at any location within operational area 102, is detected by aminimum of at least three receivers 104. A coverage area, withinoperational area 102, of each receiver 104 is defined by a combinationof the receiver's antenna pattern, the receiver alignment, and distance.When installing system 100, based upon learned experience, a firstapproximation for placement and alignment of receivers 104 is donevisually. While this is a good start, the detailed coverage area is justa guess, and accuracy of predicting receiver coverage may besignificantly degraded by various physical obstacles in the facility(e.g., the goal post).

FIG. 87 shows one exemplary static line plot 8700 illustrating a verydetailed circular Test Lap data set. This data was collected by puttingfour equally spaced barrels on a football field. Tag 101 was installedon a small motorized cart, which was attached to the first barrel by along string. System 100 was activated to create recorded data 8204 andthe cart was turned on and continuously drove in circles around thebarrel, getting closer to the barrel as the string wound around thebarrel and continuously got shorter. The same process was done for eachof the other barrels. This type of test lap data set gives a very finegrained view of coverage by each receiver 104.

FIG. 88 shows one exemplary static line plot 8800 generated by areceiver viewer 8214 and plotter 8210 of locates 8209 to display acoverage area of a particular receiver 104. Where tag 101 is traversedthroughout operational area 102, by generating plot 8800 using onlylocates 8209 resulting from receiver events 110 from a particularreceiver 104, plot 8800 shows the area of coverage for that particularreceiver 104. Thus, receiver viewer 8214 provides a simple andmethodical means of adjusting the position and orientation of receivers104 to ensure that their coverage areas all overlap sufficiently toensure uniform coverage of operational area 102.

Receiver viewer 8214 and plotter 8210 may also be used with plot 8400 ofFIG. 84, to display errors associated with receiver positioning. Thevisual error plotting within plot 8400 may indicate a specific regionwithin operational area 102 where errors are occurring because too fewreceivers 104 have coverage of that area. By using receiver viewer 8214to display the coverage area of each receiver 104, the installer mayquickly determine which receivers 104 should be adjusted to providecoverage of that region. For example, playback tool 8202 may repeatedlyreplay a portion of recorded data 8204 where receiver viewer 8214selects a different receiver, thereby showing different coverage areasfor the different receiver.

Receiver viewer 8214 is typically used with recorded data 8204, whereplayback tool 8202 repeatedly plays the recorded data back whilereceiver viewer 8214 selects one of receivers 104. A receiver livemonitor 8216 within analysis tool 8208 provides a real-time view ofbehavior of all receivers 104 simultaneously as a single tag 101 ismoved around operational area 102.

FIG. 89 shows an exemplary receiver display 8900 illustrating receivers104 used to determine a location of a single tag 101 moving withinoperational area 102. As each new data item (either a locate 8209 or anerror) for tag 101 is determined, display 8900 is updated to show thereceivers generating a receiver event 110 for tag 101. In the example ofFIG. 89, twelve receivers are used within system 100, and receivers 1,3, 4, 5, and 6 received ping 402 from tag 101. Receiver display 8900 isuseful when diagnosing problems with overlapping receiver coverage,especially in systems with larger number of receivers. By moving tagsthrough the areas of the field with spotty coverage, a user may quicklysee where intermittent coverage of specific receivers occurs.

Robotic Vehicle

The level of system knowledge, manpower, and time required to completean installation, configuration, and calibration of system 100, FIG. 1,within operational are 102 may be further reduced to simultaneouslyachieve optimal performance of the RF tag based object tracking systemand consistency of receiver coverage between installations.

A wirelessly controlled robotic vehicle carrying a tag, remotecontrolled pan and tilt (P/T) mechanisms for adjusting aim of eachreceiver and/or antenna of each receiver, and a plurality of algorithmsfor automatically controlling the robotic vehicle, automaticallyanalyzing location data, and automatically adjusting orientation of eachreceiver of the object tracking system are used to achieve optimalperformance. By automating these systems and methods, the level ofsystem knowledge, manpower, and time required to install, configure andcalibrate the object tracking system in a sporting environment issignificantly reduced. By automating the testing and adjustment of eachreceiver's aim, this may be repeated as many times as necessary toachieve optimal performance. Thus, a defined level of performance may beachieved for each installation, thereby increasing installation toinstallation consistency.

The following examples describe a step by step process for controllingmovement of the robotic vehicle within the operational area, collectingdata from the object tracking system for the tag mounted on the vehicle,analyzing that data, and automatically making adjustments to the aim ofeach receiver within the object tracking system to optimize receivercoverage of the field of play within the operational area.

FIG. 90 is a schematic showing one exemplary automated installation andcalibration (AIC) system 9000 for object tracking system 100 of FIG. 1.In this example, object tracking system 100 has twelve receivers 104,positioned within operational area 102 and around field of play 103. Inthe following example, operational area 102 is an American footballstadium and field of play 103 is an American football field. AIC system9000 includes an install/configuration controller 9070 that is incommunication with processing hub 150 and a remote controlled vehicle9080 configured with a tag 101. Remote controlled vehicle 9080 iswirelessly controlled by controller 9070 using a remote controltransmitter 9074 for example. Tag 101 periodically transmits a ping thatis detectable, when in range, by receivers 104 of object tracking system100. The location of each receiver 104 and the location of field of play103 (e.g., each corner 9012(1)-(4) of field of play 103) are accuratelymeasured and their coordinates are recorded for use by object trackingsystem 100. Once object tracking system 100 is configured, as receivers104 receive pings from one or more tags 101, processing hub 150determines locate data 120 that defines a location of the one or moretags 101 within operational area 102.

During initial installation of object tracking system 100, receivers 104are positioned around field of play 103 and each is manually aimed at apredefined location on field of play 103. For example, receiver 104(1)is manually aimed at location 9005(1), receiver 104(9) is manually aimedat location 9005(9), and so on. One goal in positioning receivers 104within operational area 102 is to enable object tracking system 100 toreliably locate tags 101 anywhere within operational area 102. Eachreceiver 104 is mounted on a remote controlled P/T mechanism 9006 thatoperates to adjust aim of receiver 104 and/or antenna 602 of receiver104. For example, P/T mechanism 9006(3) operates to aim receiver 104(3),P/T mechanism 9006(11) operates to aim receiver 104(11), and so on. Inan alternate embodiment, P/T mechanism 9006(3) operates to aim antenna602 of receiver 104(3), P/T mechanism 9006(11) operates to aim antenna602 of receiver 104(11), and so on. Each P/T mechanism 9006 is incommunication with, and controlled by, controller 9070. In thedescription of the embodiments herein below, where reference is made tothe P/T mechanism controlling aim of the receiver, the P/T mechanism mayalternatively control aim of the receiver's antenna without departingfrom the scope hereof.

Coverage Data Collection (Gross)

In a first step, controller 9070 operates object tracking system 100 todetermine location data for tracking tag 101 mounted on remotecontrolled vehicle 9080, and controls vehicle 9080 to follow apredetermined path within operational area 102. Controller 9070 receiveslocate data 120 from processing hub 150 and determines whether theinitial receiver installation configuration (i.e. mounting location andaim) meets specific criteria such that object tracking system 100 willbe able to detect tag 101 on remote controlled vehicle 9080 insubsequent steps.

FIG. 91 shows one exemplary predetermined gross path 9100 that vehicle9080 follows under control of controller 9070. Path 9100 is for exampleconsidered a “gross” path since it has reduced complexity as compared toother paths described herein. Path 9100 is defined by points 9105(1)-(4)and vehicle 9080 is controlled to travel from point 9105(1) to point9105(2), then from point 9105(2) to point 9105(3), then from point9105(3) to point 9105(4), and then from point 9105(4) to point 9105(1).Although path 9100 is shown outside and around a periphery of field ofplay 103, since points 9105 are outside of field of play 103, points9105 may be positioned elsewhere within operational area 102 withoutdeparting from the scope hereof.

FIG. 92 is a flowchart illustrating one exemplary AIC method 9200 forautomated location data collection using object tracking system 100,vehicle 9080, and tag 101 of FIG. 1. Method 9200 is for exampleimplemented within controller 9070. If method 9200 does not completesuccessfully, the installation of object tracking system 100 needsphysical evaluation and method 9200 repeated before continuing.

In step 9202, method 9200 defines a path for the vehicle to follow. Inone example of step 9202, controller 9070 generates points 9105 basedupon field of play 103 which define path 9100 for vehicle 9080 tofollow. In another example of step 9202, controller 9070 received datafor points 9105 from a user.

In step 9204, method 9200 positions the vehicle with the tag at thestart of the defined path and facing a next point in the path. In oneexample of step 9204, controller 9070 controls vehicle 9080, with tag101 attached, to stop vehicle 9080 at point 9105(1) and facing towardspoint 9105(2). In another example of step 9204, a technician positionsvehicle 9080, with tag 101 attached, at point 9105(1) and facing point9105(2) and then notifies controller 9070 that the vehicle is ready.

In step 9206, method 9200 starts collecting location data. In oneexample of step 9206, controller 9070 starts collecting locate data 120from object tracking system 100 for tag 101 and stores each collectedlocate within location data 9072. In step 9208, method 9200 starts thevehicle moving forward. In one example of step 9208, controller 9070sends a wireless signal to vehicle 9080 instructing it to move forwardcontinuously. In one example of operation, controller 9070 controlsvehicle 9080 to move forward at two meters per second.

Step 9210 is a decision. If, in step 9210, method 9200 determines thatvalid location data is received for tag 101, method 9200 continues withstep 9212; otherwise, method 9200 continues with step 9226. In oneexample of step 9210, controller 9070 determines the location of vehicle9080 from locate data 120 and considers if the location has beenreceived within the last five hundred milliseconds. In one example ofstep 9210, if controller 9070 determines that valid location data hasnot been received for tag 101 within the last five hundred milliseconds,controller 9070 aborts the current test and continues with step 9226.

In step 9212, method 9200 calculates the vehicle's movement vector usinglocation data. In one example of step 9212, controller 9070 calculates amovement vector from the last four determined locations for tag 101within locate data 120.

Step 9214 is a decision. If, in step 9214, method 9200 determines thatthe vector is right of the next point, method 9200 continues with step9216; otherwise method 9200 continues with step 9218.

In step 9216, method 9200 steers the vehicle to the left. In one exampleof step 9216, controller 9070 sends a wireless command to vehicle 9080to steer it to the left by an amount proportional to the error betweenthe vector and the direction of the next point. Method 9200 thencontinues with step 9220.

In step 9218, method 9200 steers the vehicle to the right. In oneexample of step 9218, controller 9070 sends a wireless command tovehicle 9080 to steer it to the right by an amount proportional to theerror between the vector and the direction of the next point. Method9200 then continues with step 9220.

FIG. 93 shows one exemplary scenario where vehicle 9080 is travellingfrom point 9105(2) towards point 9105(3). Arrow 406 indicates an idealpath between points 9105(2) and 9105(3). A plurality of stars 9302represent determined locations, received within locate data 120, ofvehicle 9080, and a most recent four of these locations are used tocalculate a movement vector 9304 of vehicle 9080. Since vector 9304points to the right of next point 9105(3), controller 9070 steersvehicle to the left, as indicated by arrow 9308.

Step 9220 is a decision. If, in step 9220, method 9200 determines thatthe current location of the vehicle is close to the next point in thepath, method 9200 continues with step 9222; otherwise method 9200continues with step 9210. Steps 9210 through 9220 repeat to monitor andcontrol vehicle 9080 as it progresses between each point 9105 of path9100. In one example of step 9220, as shown in FIG. 93, vehicle 9080 isconsidered close to the current destination point when it is within aradius R of that point. As shown in FIG. 93, when vehicle 9080 is withincircle 9310 it is considered close to point 9105(3). R is for example 1meter. Circle 9310 is used since even with an accurately aligned system,it is unreasonable to expect vehicle 9080 to arrive at the exactlocation of each point 9105. For example, accuracy of the determinedlocation and unevenness of the terrain typically contribute topositioning errors for vehicle 9080.

In step 9222, method 9200 selects the next point in the path. In oneexample of step 9222, controller 9070 selects point 9105(4) when thedetermined location of vehicle 9080 is within circle 9310 around point9105(3).

Step 9224 is a decision. If, in step 9224, method 9200 determines thatthe path is complete, method 9200 continues with step 9226; otherwise,method 9200 continues with step 9210. Steps 9210 through 9224 repeatuntil vehicle 9080 reaches the end point 9105 of the path 9100. Itshould be noted that in steps 9212 through 9218, vehicle 9080 isautomatically controlled to steer towards the next selected point 9105when vector 9304 does not already point towards the location of thatpoint.

In step 9226, method 9200 stops the vehicle. In one example of step9226, controller 9070 wirelessly sends a stop command to vehicle 9080.In step 9228, method 9200 stops collecting location data. In one exampleof step 9228, controller 9070 stops collecting locate data 120.

Method 9200 may be performed to collect location data using other paths,as described below.

Coverage Data Analysis (Gross)

Once method 9200 is successfully completed (i.e., vehicle 9080 reachedthe final point 9105 in path 9100), controller 9070 analyzes thecollected location data to ensure that each receiver 104 was used todetermine the location of tag 101 when vehicle 9080 was within an areaof interest (e.g., expected reception area) of the receiver. Controller9070 compares locates derived from each receiver 104 against idealreception area for that receiver 104. If controller 9070 determines thatany receiver 104 was not involved in determining any locates of tag 101when vehicle 9080 was located within the ideal reception area of thereceiver, automatic evaluation is halted until evaluation of thereceiver(s) is performed by the technician.

FIG. 94 shows one exemplary area of consideration (AOC) 9400 forreceiver 104(9) of object tracking system 100 of FIG. 1. Receiver 104(9)is used within the example of FIG. 94, but each receiver has a similarlydefined AOC 9400. Receiver 104(9) has a scope 9402 that defines angularbounds of its receiving area and a range 9404 that defines a maximumdistance from the receiver that a ping from tag 101 will be detected. Aperimeter 9414 around field of play 103 defines an operation area forobject tracking system 100. Perimeter 9414 is for example one metergreater on each side than field of play 103.

A receiver centerline 9406 of receiver 104(9) defines its desiredangular orientation 9412, that in conjunction with the location ofreceiver 104(9), scope 9402, and range 9404, define a triangular area ofideal reception for receiver 104(9). AOC 9400, shown shaded for clarityin FIG. 94, is determined as the overlap of the triangular area of idealreception with the area defined by perimeter 9414. An AOC firstcenterline 9410 aligns with receiver centerline 9406. AOC 9400 therebydefines the desired operational area of receiver 104(9) withinoperational area 102. An AOC is determined for each receiver 104 suchthat all locations within field of play 103 are covered by AOCs of atleast three receivers. Although aim of one or more receivers 104 may beautomatically adjusted, AOC 9400 for each receiver is not recalculated.

FIG. 95 is a flowchart illustrating one exemplary method 9500 forcreating a data set 9474 for each receiver 104 from location data 9072collected by method 9200 of FIG. 92. Method 9500 is for exampleimplemented within controller 9070 of FIG. 90.

In step 9502, method 9500 imports collected location data. In oneexample of step 9502, controller 9070 imports location data 9072,collected by method 9200, into working storage. In step 9504, method9500 selects a first receiver. In one example of step 9504, controller9070 selects receiver 104(9). In step 9506, method 9500 determines anAOC for the current receiver selected in step 9504. In one example ofstep 9506, controller 9070 determines AOC 9400 for receiver 104(9). Instep 9508, method 9500 creates an empty data set for the currentreceiver. In one example of step 9508, controller 9070 creates data set9474 with no entries. In step 9510, method 9500 stores receiver locatedata intersecting the receiver AOC in the data set. In one example ofstep 9510, locate data that was determined using receiver 104(9) andthat defines a locate that falls within AOC 9400 is stored within dataset 9474.

Step 9512 is a decision. If, in step 9512, method 9500 determines thatthe data set is null, method 9500 continues with step 9514; otherwisemethod 9500 continues with step 9516. In step 9514, method 9500 sends anerror message. In one example of step 9514, controller 9070 displays anerror message indicating that receiver 104(9) did not generate locationdata 9072 within its determined AOC 9400. Method 9500 then terminates.In an alternate embodiment, method 9500 continues with step 9516 andprocesses subsequent receivers such that should more than one receiver104 fail to generate locates within its determined AOC 9400, thetechnician is notified thereof.

Step 9516 is a decision. If, in step 9516, method 9500 determines thatthe current receiver is the last receiver to be processed, method 9500continues with step 9520; otherwise method 9500 continues with step9518. In step 9518, method 9500 selects a next receiver for processing.In one example of step 9518, controller 9070 selects receiver 104(10).Method then continues with step 9506. Steps 9506 through 9518 repeat foreach receiver 104 of object tracking system 100.

In step 9520, method 9500 returns a data set for each receiver. In oneexample of step 9520, controller 9070 stores data set 9474 for eachreceiver 104. Method 9500 then terminates.

Method 9500 may process collected locate data from paths other than path9100, as described in detail below.

Coverage Data Collection (Coarse)

FIG. 96 shows one exemplary predetermined coarse path 9600 that vehicle9080 follows under control of controller 9070. Path 9600 is for exampleconsidered a “coarse” path since it has more complexity that gross path9100 of FIG. 91, but less complexity as compared to fine path 10000 ofFIG. 100 described below. Path 9600 is defined by points 9605(1)-(10)and vehicle 9080 is controlled to travel from point 9605(1) to point9605(2), then from point 9605(2) to point 9605(3), and so on untilvehicle 9080 reaches point 9605(10). Although points 9605 of path 9600are positioned outside and around a periphery of field of play 103,points 9605 may be positioned elsewhere within operational area 102without departing from the scope hereof.

Controller 9070 repeats method 9200 of FIG. 92 to control vehicle 9080to follow coarse path 9600 and to collect locate data 120 from objecttracking system 100, which is stored as location data 9072 withincontroller 9070. Controller 9070 then repeats method 9500 of FIG. 95 toprocess location data 9072 and generate receiver data sets 9474.

Coverage Data Analysis and Antenna Adjustment (Coarse)

Each ping (e.g., ping 402, FIG. 4) received by receiver 104 generates areceiver event (e.g., receiver event 110, FIG. 1). Each locate generatedby object tracking system 100 is determined using at least threereceiver events for the same ping. Thus, for a location to be generatedfor a ping, at least three receivers detect the ping and generate areceiver event.

FIG. 97 is a top view of receiver 104(9) and its AOC 9400 showingexemplary distribution of locates 9702, determined using receiver eventsgenerated by receiver 104(9), between a left half 9706 and a right half9708 of AOC 9400 for determining automatic pan 9710 of receiver 104(9).In the example of FIG. 97, approximately sixty-one percent of locatesare within right half 9708, wherein pan 9710 of receiver 104(9) is madeto the left. Involving locates 9702 (indicated by circles) representslocates of receiver data set 9474 that were determined within objecttracking system 100 using receiver events generated by receiver 104(9).Non-involving locates 9704 (indicated by crosses) represent locates ofreceiver data set 9474 that were determined within object trackingsystem 100 without using information provided by receiver 104(9).Receiver 104(9) is therefore panned 9710 to the left in an attempt tobalance involving locates 9702 more evenly between halves 9706 and 9708.

FIG. 98 is a top view of receiver 104(9) and its AOC 9400 showingexemplary distribution of involving locates 9702 between a top half 9806and a bottom half 9808 of AOC 9400 for determining automatic tilt 9810of receiver 104(9). Second centerline 9802 divides AOC 9400 such thatarea of each half 9806 and 9808 are substantially equal. In the exampleof FIG. 98, approximately sixty-one percent of involving locates arewithin bottom half 9808, wherein tilt 9810 of receiver 104(9) is madeupwards. Involving locates 9702 (indicated by circles) representslocates of receiver data set 9474 that were determined within objecttracking system 100 using receiver events generated by receiver 104(9).Non-involving locates 9704 (indicated by crosses) represent locates ofreceiver data set 9474 that were determined within object trackingsystem 100 without using information provided by receiver 104(9).Receiver 104(9) is therefore tilted 9810 up in an attempt to balanceinvolving locates 9702 more evenly between halves 9806 and 9808.

FIG. 99 is a flowchart illustrating one exemplary method 9900 forautomatically adjusting orientation of receivers 104 of object trackingsystem 100. FIGS. 97, 98 and 99 are best viewed together with thefollowing description. Method 9900 is for example implemented withincontroller 9070 of AIC system 9000, FIG. 90. Upon completion of method9200 for collection location data using coarse path 9600, controller9070 invokes method 9900 to analyze each data set 9474 and automaticallyadjust orientation of each receiver 104 as necessary. Coarse path 9600is provided as an illustrative example, in practice granularity ofcoarse path 9600 is increased to improve uniformity of distribution oflocation points within each AOC 9400.

In step 9902, method 9900 selects a first receiver. In one example ofstep 9902, controller 9070 selects receiver 104(9). In step 9904, method9900 loads the receiver dataset for the current receiver. In one exampleof step 9904, controller 9070 loads receiver data set 9474 that wasgenerated by method 9200 using coarse path 9600. In step 9906, method9900 determines a percentage of locates right and left of the AOC firstcenterline and a percentage of locates above and below the AOC secondcenterline. In one example of step 9906, controller 9070 determines apercentage of locates, determined using receiver events generated byreceiver 104(9), within each of left half 9706 and right half 9708 ofAOC 9400 and determines a percentage of those locates within each of tophalf 9806 and bottom half 9808 of AOC 9400.

Step 9908 is a decision. If, in step 9908, method 9900 determines thatthe percentage of locates in the right half of the AOC is greater than apredefined threshold, method 9900 continues with step 9910; otherwise,method 9900 continues with step 9912. In one example of step 9908,controller 9070 continues with step 9910 when the determined percentageof locates within right half 9708 is greater than fifty-five percent. Instep 9910, method 9900 pans the receiver to the left by a predefinedamount. In one example of step 9910, controller 9070 commands P/Tmechanism 9006(9) to pan receiver 104(9) left by five degrees. Method9900 then continues with step 9916.

Step 9912 is a decision. If, in step 9912, method 9900 determines thatthe percentage of locates in the left half of the AOC is greater than apredefined threshold, method 9900 continues with step 9914; otherwise,method 9900 continues with step 9912. In one example of step 9912,controller 9070 continues with step 9914 when the determined percentageof locates within left half 9706 is greater than fifty-five percent. Instep 9914, method 9900 pans the receiver to the right by a predefinedamount. In one example of step 9914, controller 9070 commands P/Tmechanism 9006(9) to pan receiver 104(9) right by five degrees. Method9900 then continues with step 9916.

Step 9916 is a decision. If, in step 9916, method 9900 determines thatthe percentage of locates in the top (wider) half of the AOC is greaterthan a predefined threshold, method 9900 continues with step 9918;otherwise, method 9900 continues with step 9920. In one example of step9916, controller 9070 continues with step 9918 when the determinedpercentage of locates within top half 9806 is greater than fifty-fivepercent. In step 9918, method 9900 tilts the receiver down by apredefined amount. In one example of step 9918, controller 9070 commandsP/T mechanism 9006(9) to tilt receiver 104(9) down by one degree. Method9900 then continues with step 9924.

Step 9920 is a decision. If, in step 9920, method 9900 determines thatthe percentage of locates in the lower half of the AOC is greater than apredefined threshold, method 9900 continues with step 9922; otherwise,method 9900 continues with step 9924. In one example of step 9920,controller 9070 continues with step 9922 when the determined percentageof locates within lower half 9808 is greater than fifty-five percent. Instep 9922, method 9900 tilts the receiver up by a predefined amount. Inone example of step 9922, controller 9070 commands P/T mechanism 9006(9)to tilt receiver 104(9) up by one degree. Method 9900 then continueswith step 9924.

Step 9924 is a decision. If, in step 9924, method 9900 determines thatthe current receiver is the last receiver, method 9900 continues withstep 9928; otherwise, method 9900 continues with step 9926. In step9926, method 9900 selects the next receiver. In one example of step9926, controller 9070 selects receiver 104(10). Method 9900 thencontinues with step 9904. Steps 9904 through 9926 repeat for eachreceiver within object tracking system 100.

Step 9928 is a decision. If, in step 9928, method 9900 determines thatorientation of at least one receiver was adjusted, method 9900 continueswith step 9930; otherwise method 9900 terminates. In step 9930, method9900 invokes methods 9200 and 9500 to repeat the receiver test usingcoarse path 9600. Controller 9070 thereby repeats pan and tiltadjustment of receivers 104 until no further adjustment is needed.

Coverage Data Collection (Fine)

FIG. 100 shows one exemplary predetermined “fine” path 10000 thatvehicle 9080 follows under control of controller 9070. Path 10000 is forexample considered a “fine” path since it has more complexity thatcoarse path 9600 of FIG. 96. Path 10000 is defined by points10005(1)-(18) and vehicle 9080 is controlled to travel from point10005(1) to point 10005(2), then from point 10005(2) to point 10005(3),and so on until vehicle 9080 reaches point 10005(18). Although points10005 of path 10000 are positioned outside and around a periphery offield of play 103, points 10005 may be positioned elsewhere withinoperational area 102 without departing from the scope hereof.

Controller 9070 repeats method 9200 of FIG. 92 to control vehicle 9080to follow fine path 10000 and to collect locate data 120 from objecttracking system 100, which is stored as location data 9072 withincontroller 9070. Path 10000, as followed by vehicle 9080, is selected toinclude the entire field of play 103 in a “fine” fashion. Controller9070 then repeats method 9500 of FIG. 95 to process location data 9072and generate receiver data sets 9474.

Coverage Data Analysis and Antenna Adjustment (Fine)

Controller 9070 then repeats method 9900 of FIG. 99 to analyze coverageof field of play 103 by receivers 104, making necessary adjustments toorientation of individual receivers 104. However, during analysis ofreceiver data sets 9474 collected using fine path 10000, method 9900makes smaller (e.g., two degrees on pan and half a degree of tilt)adjustments to orientation of receivers 104 to achieve optimal systemperformance.

FIG. 101 shows vehicle 9080 of FIG. 90 in further exemplary detail.Vehicle 9080 is shown with four wheels 10102, a receiver/controller10104 that receives wireless commands, via an antenna 10106, fromcontroller 9070 and controls wheels 10102 to move and turn vehicle 9080.For example, two or more of wheels 10102 may be steerable, under controlof receiver/controller 10104, to allow controller 9070 to controlvehicle 9080 to follow each of paths 9100, 9600, and 10000 of FIGS. 91,96 and 100, respectively. Optionally, vehicle 9080 includes a mast 10108to position tag 101 at a predetermined height above the ground (e.g., asurface of field of play 103) on which vehicle 9080 travels, therebybetter simulating tags 101 attached to players in a game played on fieldof play 103. As described above, tag 101 periodically generates pings402 that propagate omnidirectionally from tag 101. Receiver/controller10104 may include other sensors (e.g., accelerometers) and functionalityfor autonomously assisting in control one or more of speed and directionof vehicle 9080.

Combination of Features

Features described above as well as those claimed below may be combinedin various ways without departing from the scope hereof. The followingexamples illustrate possible, non-limiting combinations the presentinvention has been described above, it should be clear that many changesand modifications may be made to the process and product withoutdeparting from the spirit and scope of this invention:

(A1) A trackable protection pad for use by an athlete, includes a firsttracking tag configured with the protection pad, and positioned suchthat the first tracking tag is substantially horizontal when the athleteis competing.

(A2) In the trackable protection pad denoted as (A1), the first trackingtag being positioned such that safety of the athlete is not compromised.

(A3) In either of the trackable protection pads denoted as (A1) or (A2)the first tracking tag being protected by the pad.

(A4) In any of the trackable protection pads denoted as (A1)-(A3) thefirst tracking tag being positioned to minimize line of sight blockingby the athlete.

(A5) In any of the trackable protection pads denoted as (A1)-(A4) thefirst tracking tag being positioned within the shoulder pad and as farfrom the athlete's neck and head as possible.

(A6) In any of the trackable protection pads denoted as (A1)-(A5) thetrackable protection pad further including a second tracking tagpositioned with the protection pad and separate from the first trackingtag.

(A7) In the trackable protection pads denoted as (A6) the first trackingtag being positioned on a first shoulder of the athlete and the secondtracking tag being positioned on the other shoulder of the athlete.

(A8) In either of the trackable protection pads denoted as (A6) and (A7)the separation of the first and second tracking tags permitdetermination of the orientation of the athlete.

(B1) A computer implemented tool for visually displaying performance ofan athlete tracking system that generates tracking position informationfor each signal received from a tracking tag located within a trackingarea, the tracking position information having a determined location, aposition error, and a timestamp, the tool including: a visual plottingmodule comprising machine readable instructions stored within memory andexecuted by a processor to perform, for each signal transmitted by thetracking tag, the step of: displaying a symbol on a graphicalrepresentation of the tracking area at a position representing thelocation of the tag within the tracking area, wherein the symbol isselected based upon one or more of: (a) the accuracy of the determinedlocation based upon the receiver events, and (b) errors in thedetermined location.

(B2) In the computer implemented tool denoted as (B1), the errors in thedetermined location being selected from the group including:insufficient receiver events, missing receiver events, and inconsistentreceiver events.

(B3) In either of the computer implemented tools denoted as (B1) and(B2) wherein a color of the symbol being based upon a type of the error.

(B4) In any of the computer implemented tools denoted as (B1)-(B3) asize of the symbol increasing proportional to a number of consecutiveerrors in the determined location.

(B5) In any of the computer implemented tools denoted as (B1)-(B4) thesymbol being displayed only when a selected one of a plurality ofsensors for receiving the signal is used to determine the location ofthe tag.

(B5) In any of the computer implemented tools denoted as (B1)-(B5) thetracking information being replayed at a speed substantially equal tothe speed it was recorded.

(B6) In any of the computer implemented tools denoted as (B1)-(B6) thetracking information being replayed at a speed substantially faster thanthe speed it was recorded.

(C1) A tag manager for configuring an athlete tracking system, includingsoftware, stored within memory of a portable computing device configuredwith a wireless transceiver for communicating with a tracking tagassociated with an athlete tracked by the athlete tracking system, thatwhen executed by a processor of the portable computing device implementthe steps of: automatically assigning a tag ID of the tracking tag tothe athlete within a roster list; and communicating the roster list tothe athlete tracking system.

(C2) In the tag manager denoted as (C1), the step of automaticallyassigning further comprising: generating, within the memory, a firstlist of a first plurality of tags; generating, within the memory, theroster list comprising information of the athlete; and automaticallyreading the tag ID from the tag attached to protective pads of theathlete.

(C3) In either of the tag managers denoted as (C1) and (C2), thesoftware further including instructions that when executed by theprocessor perform the step of automatically setting a configuration ofthe tag based upon the information of the athlete within the rosterlist.

(C4) In any of the tag managers denoted as (C1)-(C3), the configurationbeing set only when the tag ID is included within the roster list.

(C5) In any of the tag managers denoted as (C1)-(C4), the softwarefurther including instructions that when executed by the processorperform the step of automatically turning the tag on or off.

(C6) In any of the tag managers denoted as (C1)-(C5), the softwarefurther including instructions that when executed by the processorperform the step of automatically turning the tag off.

(C7) In any of the tag managers denoted as (C1)-(C6), the softwarefurther including instructions that when executed by the processorperform the step of automatically indicating when the tag is notassigned to the athlete.

(D1) A method for continuously evaluating performance of an athletetracking system, including: determining, using the athlete trackingsystem, the location of a test tag fixedly positioned within a trackingarea of the athlete tracking system; and determining a positioning errorof the athlete tracking system based upon a difference between thedetermined location and a known location of the test tag.

(D2) In the method denoted as (D1), the location being averaged over aplurality of consecutive determined locations of the test tag.

(D3) In either of the methods denoted as (D1) and (D2), furtherincluding generating an alert if the positioning error if greater than apredefined tolerance of the athlete tracking system.

(E1) A method for automatically optimizing performance of an objecttracking system, including: receiving, within an optimizer, locations ofeach of a plurality of tags, where each tag is attached to an objecttracked by the object tracking system; grouping identifiers of the tagswithin two or more tag sets; and configuring each tag identified withina first tag set of the two or more tag sets with a first ping rate andconfiguring tags identified within the other tags sets of the two ormore tag sets with a second ping rate. The first ping rate being higherthan the second ping rate.

(E2) In the method denoted as (E1), the first ping rate and the secondping rate being based upon a system bandwidth of the object trackingsystem, a number of tags in the first tag set and a number of tags inthe second tag set.

(E3) In either of the methods denoted as (E1) and (E2), wherein tagsidentified within the first tag set are located on a field of play andtags identified within the other tag sets are not located on the fieldof play.

(E4) In either of the methods denoted as (E1) and (E3), furtherincluding: grouping identifiers of the tags identified within the firsttag set into at least two sub-tag sets, wherein a first of the at leasttwo sub-tag sets identifies tags of objects expected to move faster thanobjects associated with tags identified within the other sub-tag sets;and determining a high ping rate for tags identified within the firstsub-tag set and a low ping rate for tags identified within other of thetwo or more sub-tag sets. The high ping rate being greater than the lowping rate and the low ping rate being greater than the second ping rate.

(E5) In any of the methods denoted as (E1)-(E4), the high ping rate andthe low ping rate being based upon a system bandwidth of the objecttracking system, a number of tags identified within the first sub-tagset, a number of tags identified within the other sub-tag sets, and anumber of tags identified within the second tag set.

(E6) In any of the methods of (E1)-(E5), the high ping rate and the lowping rate being further based upon a determined formation of objects onthe field of play.

(E7) In any of the methods of (E1)-(E6), the steps of receiving,grouping, and configuring occuring immediately prior to start of a nextplay in an American Football game.

(E8) In any of the methods of (E1)-(E7), the step of configuringincluding: generating configuration data containing the ping rate;sending the configuration data to a transmitter; and transmitting theping rate to the tag.

(E9) In any of the methods of (E1)-(E8), further including: periodicallydetermining, within the optimizer, an average number of receiver eventsper second generated by all receivers of the object tracking system; ifthe average number is greater than a predefined upper limit, decreasingthe gain of all receivers by a predefined amount; if the average numberis less than a predefined lower limit, increasing the gain of allreceivers by the predefined amount. The upper limit being equal to asystem bandwidth target (SBWT) plus a first hysteresis amount and thelower limit being equal to the SBWT minus a second hysteresis amount.

(E10) In any of the methods of (E1)-(E9), the SBWT being eighty-fivepercent of the system bandwidth.

(E11) In any of the methods of (E1)-(E5), further including:determining, within the optimizer, first, second and third receivergroups based upon the location of tags identified within the first tagset and location of the receivers; determining, within the optimizer, anaverage number of receiver events per second generated by all receiversof the object tracking system for tags identified within the first tagset; if the average number of receiver events per second is greater thana predefined upper limit, reducing system bandwidth usage by controllingreceiver gains; if the average number of receiver events per second isless than a predefined lower limit, increasing system bandwidth usage bycontrolling receiver gains. The upper limit being equal to a portion ofa system bandwidth target (SBWT) allocated to tags identified within thefirst tag set plus a hysteresis amount and the lower limit being equalto the portion of the SBWT allocated to tags identified within the firsttag set minus a hysteresis amount.

(E12)) In any of the methods of (E1)-(E11), the step of determiningreceiver groups including: determining a bounding rectangle for tagsidentified within the first tag set; determining the first receivergroup identifying four receivers of the object tracking system havinglocations that form the smallest rectangle that encompasses the boundingrectangle; determining the second receiver group identifying receiversof the object tracking system located along the sides of the rectangle;and determining the third receiver group identifying receivers of theobject tracking system not identified within either of the first andsecond group.

(E13) In any of the methods of (E1)-(E12)), the step of reducing systembandwidth usage including: if gain settings of receivers identifiedwithin the third receiver group are greater than a minimum gain setting,then decreasing the gain setting of each receiver identified within thethird receiver group; otherwise, if gain settings of receiversidentified within the second receiver group are greater than the minimumgain setting, then decreasing the gain setting of each receiveridentified within the second receiver group; and otherwise, if gainsettings of receivers identified within the first receiver group aregreater than the minimum gain setting, then decreasing the gain settingof each receiver identified within the first receiver group.

(E14) In any of the methods of (E1)-(E13), the step of increasing systembandwidth usage including: if gain settings of receivers identifiedwithin the first receiver group are less than a maximum gain setting,then increase the gain setting of each receiver identified within thefirst receiver group; otherwise, if gain settings of receiversidentified within the second receiver group are less than the maximumgain setting, then increase the gain setting of each receiver identifiedwithin the second receiver group; and otherwise, if gain settings ofreceivers identified within the third receiver group are greater thanthe maximum gain setting, then increasing the gain setting of eachreceiver identified within the third receiver group.

(E15) In any of the methods of (E1)-(E14), further including:periodically determining, within the optimizer, a locate-to-ping ratiobased upon a number of pings transmitted by the plurality of tags duringa sample period and a number of locates resulting within the objecttracking system from these pings; and if the locate-to-ping ratio isbelow a predefined threshold, increasing tolerance of post-locatefilters of the object tracking system.

(E16) In any of the methods of (E1)-(E15), the step of increasingtolerance including increasing a convergence threshold of a post-locateconvergence filter, wherein the post-locate convergence filter discardslocates determined from receiver events from four or more differentreceivers of the object tracking system when a convergence value of thelocate is above the convergence threshold.

(E17) In any of the methods of (E1)-(E16), the step of increasingtolerance comprising increasing a four receiver threshold of apost-locate bounding box filter, wherein the post-locate bounding boxfilter discards locates having a location outside of a bounding boxdefined by the location of at least four receivers used to determine thelocate and further based upon the four receiver threshold and a distanceof the locate from a boundary of the bounding box.

(E18) In any of the methods of (E1)-(E17), the step of increasingtolerance comprising increasing a three receiver threshold of apost-locate bounding box filter, wherein the post-locate bounding boxfilter discards locates having a location outside of a bounding boxdefined by the location of only three receivers when only threereceivers are used to determine the locate and further based upon thethree receiver threshold and a distance of the locate from a boundary ofthe bounding box.

(E19) In any of the methods of (E1)-(E19), the step of increasingtolerance comprising setting a three locate enable to true wherein areceiver count filter is prohibited from discarding locates determinedfrom only three receivers.

(F1) An self-configurable tracking tag for determining location of anobject, including: a processor; a transmitter for transmitting, undercontrol of the processor, pings at a ping rate and that are detectableby an object tracking system; a movement sensor coupled with theprocessor for sensing movement of the tracking tag; and a memory storingan algorithm comprising machine readable instructions that when executedby the processor perform the steps of: determining, using the movementsensor, movement of the tag; and adjusting the ping rate based upon themovement.

(F2) In the self-configurable tracking tag denoted as (F1), thealgorithm implementing one or more of simple linear relationship, athresholded relationship, a weighted relationship, and a non-linearrelationship.

(F3) In either of the self-configurable tracking tags denoted as (F1)and (F2), the algorithm increasing the ping rate as the determinedmovement increases.

(F4) In any of the self-configurable tracking tags denoted as (F1)-(F3),the algorithm decreasing the ping rate as the determined movementdecreases.

(G1) A method for automatically optimizing performance of an objecttracking system having a plurality of receivers for receiving pingsignals from a plurality of tags, wherein each tag is attached to anobject tracked by the object tracking system, including: receiving,within an optimizer, locations of each of the plurality of tags;grouping identifiers of the tags within two or more tag sets, wherein afirst of the tag sets identifies tags attached to objects involved in asituation of interest; determining, within the optimizer, a firstreceiver group based upon the location of tags identified within thefirst tag set and location of each of the plurality of receivers;determining a center of a smallest 3D polygonal shape bounding thelocations of tags identified in the first tag set; and incrementallymoving aim of an antenna of each receiver within the first receivergroup towards the center while a number of receiver events per secondgenerated by the receiver for tags identified within the first tag setincreases.

(G2) In the method denoted as (G1), further including: determining,within the optimizer, a second receiver group based upon the location oftags identified within the first tag set and location of each of theplurality of receivers; and incrementally moving aim of an antenna ofeach receiver within the second receiver group towards the center whilea number of receiver events per second generated by the receiver fortags identified within the first tag set increases.

(G3) In either of the methods denoted as (G1) and (G2), the step ofincrementally moving including: first panning the antenna of eachreceiver within the first receiver group towards the center while anumber of receiver events per second generated by the receiver for tagsidentified within the first tag set increases; and then tilting theantenna of each receiver within the first receiver group towards thecenter while a number of receiver events per second generated by thereceiver for tags identified within the first tag set increases.

(G4) In any of the methods denoted as (G1)-(G3), the step ofincrementally moving comprising moving aim of the antenna back to animmediately previous position when the number of receiver events persecond generated by the receiver for tags identified within the firsttag set does not increase.

(H1) A method for optimizing performance of an object tracking system,including: determining a number of receiver events per second generatedby a receiver of the object tracking system; and controlling thereceiver to switch between an analog front end without a filter and ananalog front end with a filter based upon the receiver events persecond.

(H2) In the method denoted as (H1), the step of controlling including:determining whether the number of receiver events per second is within apredefined limit; and controlling the receiver to switch to using theanalog front end with the filter when the number of receiver events persecond is not within the predefined limit.

(H3) In either of the methods denoted as (H1) and (H2), furtherincluding repeating the steps of determining and controlling for eachreceiver of the object tracking system.

(I1) A reconfigurable receiver for use within an object tracking system,including: a plurality of analog front ends, each generating a digitalsignal; a digital back end for processing one of the digital signals;and a digital switch for selecting, under control of the digital backend, the one digital signal.

(I2) In the reconfigurable receiver denoted as (I1), each of theplurality of analog front ends including: an antenna having a desiredrange and scope for receiving a ping transmitted by an RF tag tracked bythe object tracking system and outputting an analog signal; andconditioning and converting circuitry for conditioning the analog signaland converting the conditioned analog signal to the digital signal.

(I3) In either of the reconfigurable receivers denoted as (I1) and (I2),the digital back end comprising an interface for (a) receiving a commandfrom a remote device to select the one digital signal, and (b)controlling the digital switch to select the one digital signal.

(I4) In any of the reconfigurable receivers denoted as (I1)-(I3), thecommand being received from an optimizer of an object tracking system todynamically modify characteristics of the receiver during operation.

(I5) In any of the reconfigurable receivers denoted as (I1)-(I4), theobject tracking system including a plurality of receivers and whereinthe steps of determining a location and controlling are repeated foreach of the plurality of receivers.

(I6) In any of the reconfigurable receivers denoted as (I1)-(I5), one ofthe plurality of analog front ends further including a band pass filterpositioned between the antenna and the conditioning and convertingcircuitry.

(I7) In any of the reconfigurable receivers denoted as (I1)-(I6), theobject tracking system including a plurality of receivers and the stepsof determining a location and controlling repeating for each of theplurality of receivers.

(J1) A method for optimizing performance of an object tracking system,including:

determining, within an optimizer configured with the object trackingsystem, a bounding rectangle for locations of RF tags attached toobjects of interest; determining, within the optimizer, a location ofthe bounding rectangle relative to a location of a receiver of theobject tracking system; and controlling, from the optimizer, thereceiver to switch from a first analog front end to a second analogfront end based upon the relative location of the bounding rectangle.The first analog front end is configured with a first range and a firstscope and the second analog front end is configured with a second rangethat is different from the first range and a second scope that isdifferent from the second scope.

(J2) In the method denoted as (J1), the object tracking system includinga plurality of receivers wherein the steps of determining a location andcontrolling are repeated for each of the plurality of receivers.

(J3) In the methods denoted as either (J1) or (J2), the receiverincluding at least three selectable analog front ends each havingdifferent range and/or scope from any other of the at least three analogfront ends.

(K1) An automated installation and calibration (AIC) system for anobject tracking system, including: a wirelessly controlled vehicle; anRF tag configured with the vehicle; and a controller for (a) receivinglocation data for the RF tag from the object tracking system, (b)controlling the vehicle to follow a path based upon the location data,and (c) adjusting orientation of at least one receiver of the objecttracking system based upon analysis of the location data associated withthe receiver.

(K2) In the AIC system denoted as (K1), the receiver being mounted on aremote controlled pan and tilt mechanism, the controller commanding thepan and tilt mechanism to adjust the orientation of the receiver.

(K3) In the AIC systems denoted as either (K1) or (K2), the RF tagperiodically generating a ping that is detected by the object trackingsystem to generate the location data.

(L1) An automated installation and calibration method for an objecttracking system, including: receiving location data generated by theobject tracking system for an RF tag attached to a wirelessly controlledvehicle; controlling movement of the vehicle to follow a path based uponthe location data; determining a data set of locates from the locationdata based upon an area of consideration for a receiver of the objecttracking system; and adjusting the orientation of the receiver basedupon analysis of the data set.

(L2) In the method denoted as (L1), the step of controlling includingcontrolling the vehicle to follow the path at a constant speed.

(L3) In the methods denoted as either (L1) or (L2), the path beingselected from one of a gross path, a coarse path, and a fine path,wherein the coarse path is more complex than the gross path and lesscomplex than the fine path.

(L4) In any of the methods denoted as (L1)-(L3), wherein the steps ofreceiving, controlling, determining and adjusting are repeated for atleast two of the gross path, the coarse path, and the fine path.

(L5) In any of the methods denoted as (L1)-(L4), the area ofconsideration being defined by at least two of a range of the receiver,a scope of the receiver, and an operational area of the object trackingsystem.

(L6) In any of the methods denoted as (L1)-(L5), the step of determiningincluding determining whether each locate within the location data islocated within the area of consideration.

(L7) In any of the methods denoted as (L1)-(L6), the step of adjustingincluding determining a percentage of locates, generated by the objecttracking system using receiver events from the receiver, that arelocated in one half of the area of consideration.

(L8) In any of the methods denoted as (L1)-(L7), the step of adjustingincluding panning the receiver when the one half is one of a left and aright half of the area of consideration.

(L9) In any of the methods denoted as (L1)-(L8), the step of adjustingincluding tilting the receiver when the one half is one of a top and abottom half of the area of consideration.

(M1) A software product including instructions, stored on non-transitorycomputer-readable media, wherein the instructions, when executed by acomputer, perform steps for automating installation and calibration ofan object tracking system, comprising: instructions for receivinglocation data generated by the object tracking system for an RF tagattached to a wirelessly controlled vehicle; instructions forcontrolling movement of the vehicle to follow a path based upon thelocation data; instructions for determining a data set of locates fromthe location data based upon an area of consideration for a receiver ofthe object tracking system; and instructions for adjusting theorientation of the receiver based upon analysis of the data set.

(M2) In software product denoted as (M1), the instructions forcontrolling including instructions for controlling the vehicle to followthe path at a constant speed.

(M3) In software products denoted as either (M1) or (M2), the path beingselected from one of a gross path, a coarse path, and a fine path. Thecoarse path is more complex than the gross path and less complex thanthe fine path.

(M4) In any of the software products denoted as (M1)-(M3), theinstructions for receiving, controlling, determining and adjusting arerepeated for at least two of the gross path, the coarse path, and thefine path.

Changes may be made in the above methods and systems without departingfrom the scope hereof. It should thus be noted that the matter containedin the above description or shown in the accompanying drawings should beinterpreted as illustrative and not in a limiting sense. The followingclaims are intended to cover all generic and specific features describedherein, as well as all statements of the scope of the present method andsystem, which, as a matter of language, might be said to falltherebetween.

What is claimed is:
 1. A method for automatically optimizing performanceof an object tracking system, comprising: receiving, within anoptimizer, respective locations of a plurality of tags, wherein each tagis attached to an object tracked by the object tracking system; groupingidentifiers of the tags within two or more tag sets based upon thelocations; and configuring each tag identified within a first tag set ofthe two or more tag sets with a first ping rate and configuring tagsidentified within each other one of the two or more tag sets with asecond ping rate less than the first ping rate.
 2. The method of claim1, further comprising determining the first ping rate and the secondping rate based upon a system bandwidth of the object tracking system,number of tags in the first tag set, and number of tags in the other ofthe two or more tag sets.
 3. The method of claim 1, the first tag setidentifying tags located on a field of play and the other of the two ormore tag sets identifying tags not located on the field of play.
 4. Themethod of claim 1, further comprising: grouping identifiers of the tagsidentified within the first tag set into at least two sub-tag sets,wherein a first of the at least two sub-tag sets identifies tags ofobjects expected to move faster than objects associated with tagsidentified within each other one of the at least two sub-tag sets;configuring each tag identified within the first sub-tag set with a highping rate; and configuring each tag identified in the other of the atleast two sub-tag sets with a low ping rate that is smaller than thehigh ping rate and greater than the second ping rate.
 5. The method ofclaim 4, further comprising determining the high ping rate and the lowping rate based upon a system bandwidth of the object tracking system,number of tags identified within the first sub-tag set, number of tagsidentified within the other of the two or more sub-tag sets, and numberof tags identified within the second tag set.
 6. The method of claim 5,the step of determining further comprising determining the high pingrate and the low ping rate based upon a determined formation of objectscorresponding to tags identified within the first tag set.
 7. The methodof claim 1, the steps of receiving, grouping, and configuring occurringimmediately prior to start of a next play in an American Football game.8. The method of claim 1, the step of configuring comprisingtransmitting the first ping rate to each tag identified within the firsttag set and transmitting the second ping rate to tags identified withineach other one of the two or more tag sets.
 9. The method of claim 1,further comprising: periodically determining, within the optimizer, anaverage number of receiver events per second generated by all receiversof the object tracking system; if the average number is greater than apredefined upper limit, decreasing a gain setting of all receivers by apredefined amount; if the average number is less than a predefined lowerlimit, increasing the gain setting of all receivers by the predefinedamount; wherein the predefined upper limit is equal to a systembandwidth target (SBWT) plus a first hysteresis amount and thepredefined lower limit is equal to the SBWT minus a second hysteresisamount.
 10. The method of claim 9, wherein the SBWT is 85% of a systembandwidth of the object tracking system.
 11. The method of claim 1,further comprising: determining, within the optimizer, average number ofreceiver events per second generated by all receivers of the objecttracking system for tags identified within the first tag set; reducingsystem bandwidth usage when the average number of receiver events persecond is greater than a predefined upper limit; and increasing systembandwidth usage when the average number of receiver events per second isless than a predefined lower limit; the predefined upper limit beingequal to a portion of a system bandwidth target (SBWT) allocated to tagsidentified within the first tag set plus a first hysteresis amount andthe predefined lower limit being equal to the portion of the SBWTallocated to tags identified within the first tag set minus a secondhysteresis amount.
 12. The method of claim 11, further comprising:determining a bounding rectangle that includes the locations of tagsidentified within the first tag set; identifying four of the receiversof the object tracking system who's locations defines the smallestrectangle that encompasses the bounding rectangle to form a firstreceiver group; identifying receivers of the object tracking systemlocated along the sides of the smallest rectangle to form a secondreceiver group; and identifying receivers of the object tracking systemnot identified within either of the first receiver group and the secondreceiver group to form a third receiver group.
 13. The method of claim12, the step of reducing system bandwidth usage comprising: if gainsettings of receivers identified within the third receiver group aregreater than a minimum gain setting, then decreasing the gain setting ofeach receiver identified within the third receiver group; otherwise, ifgain settings of receivers identified within the second receiver groupare greater than the minimum gain setting, then decreasing the gainsetting of each receiver identified within the second receiver group;and otherwise, if gain settings of receivers identified within the firstreceiver group are greater than the minimum gain setting, thendecreasing the gain setting of each receiver identified within the firstreceiver group.
 14. The method of claim 12, the step of increasingsystem bandwidth usage comprising: if gain settings of receiversidentified within the first receiver group are less than a maximum gainsetting, then increasing the gain setting of each receiver identifiedwithin the first receiver group; otherwise, if gain settings ofreceivers identified within the second receiver group are less than themaximum gain setting, then increasing the gain setting of each receiveridentified within the second receiver group; and otherwise, if gainsettings of receivers identified within the third receiver group areless than the maximum gain setting, then increasing the gain setting ofeach receiver identified within the third receiver group.
 15. The methodof claim 1, further comprising: periodically determining, within theoptimizer, a locate-to-ping ratio based upon number of pings transmittedby the plurality of tags during a sample period and number of locatesresulting within the object tracking system from the pings; andincreasing tolerance of post-locate filters of the object trackingsystem when the locate-to-ping ratio is below a predefined threshold.16. The method of claim 15, the step of increasing tolerance ofpost-locate filters comprising increasing a convergence threshold of apost-locate convergence filter that discards locates determined fromreceiver events derived from four or more different receivers of theobject tracking system that have a convergence value above theconvergence threshold.
 17. The method of claim 15, the step ofincreasing tolerance of post-locate filters comprising increasing a fourreceiver threshold of a post-locate bounding box filter that discardslocates having a location outside of a bounding box defined by locationsof at least four receivers used to determine the locate based upon thefour receiver threshold and a distance of the locate from a boundary ofthe bounding box.
 18. The method of claim 15, the step of increasingtolerance of post-locate filters comprising increasing a three receiverthreshold of a post-locate bounding box filter that, when only threereceivers are used to determine the locate, discards locates having alocation outside of a bounding box defined by locations of the onlythree receivers based upon the three receiver threshold and a distanceof the locate from a boundary of the bounding box.
 19. The method ofclaim 15, the step of increasing tolerance of post-locate filterscomprising setting a three locate enable to true to prohibit a receivercount filter discarding locates determined from only three receivers.20. A non-transitory computer-readable media having instructions that,when executed by a computer, perform steps for automatically optimizingperformance of an object tracking system, comprising: instructions forreceiving, within an optimizer, respective locations of a plurality oftags, wherein each tag is attached to an object tracked by the objecttracking system; instructions for grouping identifiers of the tagswithin two or more tag sets based upon the locations; and instructionsfor configuring each tag identified within a first tag set of the two ormore tag sets with a first ping rate and configuring tags identifiedwithin each other one of the two or more tag sets with a second pingrate less than the first ping rate.
 21. An optimizer for automaticallyoptimizing performance of an object tracking system, comprising: aprocessor; a memory; software, stored within the memory, comprisingmachine readable instructions that when executed by the processorperform the steps of: receiving, within an optimizer, respectivelocations of a plurality of tags, wherein each tag is attached to anobject tracked by the object tracking system; grouping identifiers ofthe tags within two or more tag sets based upon the locations; andconfiguring each tag identified within a first tag set of the two ormore tag sets with a first ping rate and configuring tags identifiedwithin each other one of the two or more tag sets with a second pingrate less than the first ping rate.
 22. The optimizer of claim 21, thefirst ping rate and the second ping rate being at least partially basedupon a determined formation of objects on the field of play.
 23. Amethod for optimizing performance of an object tracking system,comprising: determining number of receiver events per second generatedby a receiver of the object tracking system; and controlling thereceiver to switch between an analog front end without a filter and ananalog front end with a filter based upon the receiver events persecond.
 24. The method of claim 23, the step of controlling comprising:determining whether the number of receiver events per second is within apredefined limit; and controlling the receiver to switch to using theanalog front end with the filter when the number of receiver events persecond is not within the predefined limit.
 25. The method of claim 23,further comprising repeating the steps of determining and controllingfor each of a plurality of receivers of the object tracking system. 26.A method for automatically optimizing performance of an object trackingsystem, comprising: receiving, within an optimizer, respective locationsof a plurality of tags, wherein each tag is attached to an objecttracked by the object tracking system; configuring each tag located on afield of play with a first ping rate; and configuring each tag notlocated on the field of play with a second first ping rate less than thefirst ping rate.
 27. The method of claim 26, the step of configuringcomprising transmitting the first ping rate to each tag located on thefield of play and transmitting the second ping rate to tags not locatedon the field of play.